Machine Learning Engineer Jobs

Our client, a leading financial services company, are hiring a C++ Quantitative Research Engineer to join the team in New York City. The successful candidate will collaborate with quantitative researchers, engineers and traders to build high-performance applications, research platforms and trading systems that uncover and capture opportunities across global financial markets.


Responsibilities

• Develop and maintain high-performance applications using modern C++.

• Engineer low-latency systems capable of processing and normalising large volumes of market data.

• Integrate data feeds across global exchanges, vendors and multiple asset classes.

• Design and optimise high-frequency trading and execution platforms.

• Create scalable analytics libraries for quantitative research and real-time forecasting.

• Develop research tools using advanced statistical and machine learning technologies.

• Translate quantitative models into reliable, production-ready systems.

• Enhance the speed, resilience and accuracy of critical live-market platforms.

• Build and monitor distributed systems and complex data-processing pipelines.

• Partner with quantitative researchers, traders and engineers to deliver commercially valuable solutions.

Skillset

• Bachelor's, master's degree or PhD in Computer Science, Computer Engineering, Mathematics, Physics or similar.

• Extensive software engineering experience, including the development of production-grade systems using C++.

• Strong knowledge of modern C++, low-latency engineering and performance optimisation.

• Experience creating reliable, maintainable and high-performance software for business-critical environments.

• A thorough understanding of distributed systems, scalable architecture and complex data-processing pipelines.

• Ability to assess interconnected systems from first principles and deliver effective improvements.

• Experience enhancing established production platforms and designing new systems from the ground up.

• A rigorous approach to software correctness, system resilience, monitoring and fail-safe engineering.

Benefits

• Salary: $275k - $350k

• Performance bonus.

Our client, an AI-driven FinTech company, is hiring a graduate or early-career Software Engineer to join their team in New York. The successful candidate will build and develop production-grade AI agent systems that solve complex, real-world financial challenges, while also taking ownership across context engineering, prompting, tooling, evaluations, guardrails, infrastructure and the broader product experience.


Responsibilities

• Design, build and deploy reliable AI agents for finance and audit workflows, with strong verification, guardrails, observability and evaluation frameworks.

• Develop context-engineering strategies that enable AI systems to reason effectively across transactions, ledgers, contracts, policies and historical financial decisions.

• Build robust data pipelines that ingest, standardise, reconcile and process information from ERPs, banking systems, payroll, billing platforms, CRMs and other enterprise applications.

• Develop AI agents capable of explaining decisions, recognising uncertainty, escalating exceptions and improving through human feedback.

• Design resilient, long-running agentic workflows that operate reliably across complex, stateful and interconnected enterprise systems.

• Build secure and fully traceable mechanisms for writing AI-driven actions back to financial systems of record, ensuring accuracy and auditability.

• Contribute across the full technology stack, including LLM systems, backend engineering, infrastructure, data and user-facing product development.

• Leverage modern AI development and coding tools to accelerate delivery while maintaining high standards of engineering quality and reliability.

• Collaborate directly with CFOs, controllers, accountants, and finance teams to understand operational challenges and translate them into production-ready solutions.

• Take ownership of technical decisions, feature development and delivery, independently driving work from initial problem definition through to production.

Skillset

• Currently completing a Bachelor's or Master's degree or recently graduated, ideally in Computer Science, Machine Learning, Artificial Intelligence or similar.

• At least one meaningful internship in software engineering, machine learning or AI engineering, with exposure to building real-world technology.

• Practical experience developing AI agents, LLM-powered applications, or generative AI systems through professional experience, research, academic work or personal projects.

• Good understanding of prompt engineering, context engineering, tool use, model evaluation, verification and AI agent reliability.

• Hands-on experience using AI-assisted development tools such as Claude Code, Cursor or similar coding agents.

• Strong software engineering fundamentals with proficiency in Python or another modern programming language, such as C++, Java, Go or Rust.

• Ability to quickly learn unfamiliar technologies and domains and translate complex business workflows into effective software solutions.

• Comfortable contributing across multiple areas of the technology stack, including backend engineering, infrastructure, AI/LLM systems and product development.

• A proactive, ownership-driven approach, with strong problem-solving skills, curiosity and the ability to independently scope and deliver work.

• Evidence of building and delivering substantial technical projects, such as production applications, research prototypes, open-source contributions, side projects or hackathon solutions.

Benefits

• Salary: $130k - $140k

• Equity:

• Comprehensive medical, dental, and vision insurance.

• 401(k) match.

Our client is a venture-backed fintech startup, is hiring a Senior AI Engineer to join the team full-time in New York. The successful candidate will take end-to-end ownership of the company's AI capabilities, from models and data pipelines to evaluation, observability and production standards, while also helping shape the future direction of its AI function and team.


Responsibilities

• Design, build and deploy LLM-powered systems that extract structured data from complex documents across multiple formats.

• Develop detailed source citation, confidence-scoring and human-in-the-loop review capabilities to ensure outputs are accurate and traceable.

• Build entity-resolution systems that reconcile information from banks, credit bureaus, government agencies, courts and family-provided records.

• Convert structured estate data into accurate, court-ready documents and filings.

• Create robust evaluation frameworks, ground-truth datasets, and automated regression tests for production AI systems.

• Implement monitoring and observability tools to track model quality, reliability, latency and cost.

• Develop intelligent routing strategies across multiple model providers, balancing accuracy, performance and cost.

• Own the underlying AI infrastructure, including data pipelines, retrieval systems, vector databases and deployment workflows.

• Establish the technical, evaluation and quality standards used to determine when AI capabilities are ready for production.

• Help build and scale the company's AI engineering function, shaping its technical direction, processes and future team.

Skillset

• Proven experience designing, building and deploying production-grade LLM or machine learning systems used by real customers.

• Hands-on experience with document intelligence, information extraction, RAG, AI agents or similar AI applications.

• Experience developing technology in high-stakes environments where accuracy, traceability, compliance and reliability are essential.

• Strong understanding of model evaluation, including how to measure performance, validate outputs and make AI-generated decisions explainable and defensible.

• Advanced proficiency in Python.

• Practical experience building and maintaining production data and AI pipelines.

• Strong knowledge of vector databases, retrieval architectures, model evaluation techniques and routing across multiple LLM providers.

• Ability to independently own the supporting AI infrastructure without relying on a dedicated platform team.

• Experience as a founding or early-stage engineer, technical founder, first AI/ML hire, or someone who has established an AI function within a growing company is highly valued.

Benefits

• Salary: $150k - $250k DOE.

• Meaningful equity.

• Medical, Dental and Vision insurance.

Our client, an early-stage AI startup, is hiring a Founding Engineer to join the team in New York. The successful candidate will play a key role in shaping both the product vision and technical direction of the business, building cutting-edge AI systems that accelerate scientific discovery through intelligent automation, multimodal machine learning and advanced data platforms.


Responsibilities

• Design, develop and deploy enterprise-grade AI solutions that empower scientific teams.

• Build advanced multimodal AI systems, including computer vision models, speech-to-text capabilities and intelligent AI agents.

• Develop scalable machine learning pipelines and data infrastructure to support scientific applications.

• Create AI models that analyze experimental data, uncover insights, predict outcomes and optimize processes.

• Convert complex laboratory data into structured, high-quality datasets for machine learning development.

• Work closely with research partners and customers to gather feedback, validate solutions and continuously improve products.

• Shape the company's technical architecture, engineering practices and long-term AI roadmap.

• Partner with founders and scientific leaders to drive product development and technical decision-making.

• Deliver robust, production-ready software with a focus on speed, quality and scalability.

Skillset

• Proven experience designing, building and deploying production software within a startup, research environment or leading technology organization.

• Strong machine learning expertise with deep knowledge in at least two of the following areas: Geometric Deep Learning, Graph Neural Networks (GNNs), Diffusion Models, Generative AI or ML Interatomic Potentials.

• Experience developing and delivering AI-powered products that solve real-world customer challenges.

• Strong software engineering capabilities across backend development, machine learning infrastructure and cloud-based environments.

• Hands-on experience building scalable data pipelines, ML workflows and production AI systems.

• Ability to take ownership across the entire product lifecycle, from initial concept and experimentation through to deployment and optimization.

• Comfortable working in a fast-paced startup environment with a high level of autonomy, ownership and accountability.

• Strong analytical, problem-solving and communication skills with the ability to collaborate across technical and scientific teams.

Benefits

• Salary: $150k - $220k DOE.

Our client, an innovative AI and Data company, is hiring a Head of Research to join the team in New York. The successful candidate will transform unique consumer-generated data streams into a gold standard for AI training and evaluation by shaping the company's research strategy, collaborating directly with leading AI labs, and establishing the organization as a recognised authority in audio data research and evaluation science.


Responsibilities

• Define and drive the company's AI research strategy, focusing on data evaluation, AI oversight and generative AI innovation.

• Develop strategic partnerships with leading AI research labs, academic institutions and industry experts.

• Build AI-assisted evaluation frameworks to measure, validate, and enhance audio and multimodal datasets.

• Translate emerging AI research advancements into scalable data solutions and production-ready capabilities.

• Position the organization as a recognized leader in audio AI, speech intelligence and AI evaluation science.

• Design and execute rigorous machine learning experiments, benchmarks and evaluation methodologies to support next-generation AI models.

• Represent the company across the global AI research ecosystem, building relationships with researchers, partners and technical communities.

• Collaborate with product and engineering teams to define AI data strategies, research priorities and innovation roadmaps.

Skillset

• Proven track record of impactful AI/ML research focused on data evaluation, generative AI or AI oversight.

• Deep expertise in audio, speech or multimodal AI systems, with strong understanding of emerging research trends.

• Experience working with frontier AI models, training pipelines and evaluation frameworks.

• Strong knowledge of AI evaluation methodologies, benchmarking and AI-assisted evaluation approaches.

• Experience designing and executing rigorous machine learning experiments using Python and PyTorch.

• Ability to translate complex AI research concepts into scalable, production-ready data solutions.

• Strong understanding of data quality, dataset development and evaluation strategies for AI model improvement.

• Proven ability to build relationships with leading AI researchers, technical partners and industry stakeholders.

• Strong communication skills with the ability to represent research concepts and technical insights to diverse audiences.

• Founder mindset with the ability to operate independently, drive innovation and deliver impact in a fast-moving environment.

Benefits

• Salary: $250k - $300k

• Comprehensive benefits package.

Our client, an innovative AI and Data company, is hiring a Data Operations Lead to join the team in New York. The successful candidate will own the end-to-end data lifecycle, shaping data operations, developing scalable processes, managing external partners and ensuring the highest standards of dataset quality to deliver high-quality, production-ready datasets for leading AI research teams.


Responsibilities

• Own the end-to-end delivery of high-quality AI training datasets, from raw audio data collection through to production-ready outputs.

• Collaborate with AI research teams and external partners to define, manage and deliver dataset requirements.

• Support the development and execution of commercial data agreements, ensuring successful delivery against customer expectations.

• Design, build and optimize operational workflows across transcription, annotation, quality assurance and dataset production.

• Develop robust data quality frameworks, acceptance criteria and validation processes to maintain delivery standards.

• Lead outsourced and international data operations teams, ensuring quality, efficiency and timely delivery.

• Partner with engineering teams to enhance data pipelines, tooling and operational scalability.

• Identify and implement improvements to increase dataset quality, reliability and operational efficiency.

• Serve as a key liaison between customers, internal stakeholders, engineering teams and external vendors.

• Contribute to the company's data strategy and help scale data operations as the organization grows.

Skillset

• Minimum of 5 years of experience building and scaling data operations, data pipelines or AI/ML data workflows.

• Proven experience working with audio, speech or multimodal datasets within AI or machine learning environments.

• Strong track record managing external data partnerships, dataset delivery and AI training data programs.

• Experience leading global or outsourced teams focused on data annotation, transcription and quality assurance.

• Strong understanding of data quality frameworks, validation processes and operational performance metrics.

• Technical proficiency across data pipelines, cloud infrastructure and AI/ML workflows.

• Knowledge of digital audio fundamentals, including sample rates, voice activity detection (VAD) and audio processing formats.

• Experience developing or managing AI training datasets for applications such as ASR, TTS, speaker identification or conversational AI.

• Familiarity with audio processing and data tools such as Librosa, FFmpeg, SoX, torchaudio, and cloud platforms including AWS, GCP or Azure.

• Entrepreneurial mindset with the ability to thrive in a fast-paced environment, take ownership and make decisions with limited information.

Benefits

• Salary: $180k - $220k

• Comprehensive benefits package.

Our client, a growing FinTech company, are hiring an AI Engineer to join their team in Colorado. The successful candidate will architect, develop and scale enterprise-grade multi-agent AI systems, taking ownership of complex solutions from initial design through to production deployment to shape the future of agentic AI within the financial services industry.


Responsibilities

• Design and develop production-ready multi-agent AI systems using modern agent frameworks and architectures.

• Build intelligent AI workflows that integrate retrieval, reasoning, tool execution, validation and compliance controls.

• Develop scalable distributed services to support reliable agent execution, monitoring and fault tolerance.

• Create evaluation frameworks to assess reasoning performance, accuracy, groundedness, hallucination mitigation and financial correctness.

• Implement robust memory management, context handling and agent state persistence solutions.

• Collaborate with Product, Design and Engineering teams to translate business requirements into scalable AI solutions.

• Optimise AI systems for performance, latency, scalability, reliability and cost efficiency.

• Shape architectural decisions across model serving, vector databases, orchestration platforms, caching strategies and cloud infrastructure.

Skillset

• At least 6 years' experience in Machine Learning, including 3 years building and deploying Generative AI and LLM-powered applications in production environments.

• Demonstrated experience designing, developing, and deploying multi-agent AI systems.

• Deep expertise across multimodal LLMs, agent frameworks, knowledge graphs, reinforcement learning, model fine-tuning, agent memory and data synthesis techniques.

• Advanced Python programming skills with strong experience using modern AI and machine learning frameworks.

• Proven experience building distributed systems and deploying cloud-native applications across AWS, GCP or Azure.

• Experience developing monitoring, evaluation, and reliability frameworks to ensure the performance and safety of AI systems.

• Strong architectural and systems-thinking capabilities, with the ability to design scalable, multi-component AI platforms.

• Experience working in high-growth, fast-paced, or early-stage startup environments is highly desirable.

Benefits

• Salary: $200k - $275k

• Comprehensive benefits package.

Our client, a growing FinTech company, are hiring a Staff Machine Learning Engineer to join their team in Colorado. The successful candidate will play a key role in designing and building production-grade, multi-agent AI systems that power advisor copilots, investment intelligence, workflow automation and autonomous research.


Responsibilities

• Design, develop and deploy production-grade multi-agent AI systems using modern agent frameworks and large language models (LLMs).

• Build intelligent AI workflows that combine context retrieval, reasoning, tool execution, validation and compliance controls.

• Develop scalable distributed services for agent orchestration, with a focus on observability, monitoring, resilience and fault tolerance.

• Create evaluation frameworks to assess reasoning quality, accuracy, groundedness, hallucination mitigation and financial correctness.

• Implement scalable approaches to memory management, context handling and persistent agent state.

• Collaborate closely with Product, Design and Engineering teams to translate business requirements into scalable AI solutions.

• Continuously optimize AI systems for performance, latency, reliability, scalability and cost efficiency.

• Influence the design and evolution of AI infrastructure, including model serving, orchestration, vector databases, caching and cloud-native architecture.

Skillset

• At least 6 years of experience in Machine Learning, including 2-3 years building and deploying Generative AI or LLM-powered applications in production environments.

• Proven experience designing, developing and implementing production-ready multi-agent AI systems.

• Strong expertise in multimodal LLMs, agent frameworks, knowledge graphs, reinforcement learning, model fine-tuning, agent memory and synthetic data generation.

• Advanced Python programming skills with hands-on experience using modern AI and machine learning frameworks.

• Experience building distributed systems and deploying cloud-native applications across AWS, Azure or Google Cloud Platform (GCP).

• Strong understanding of AI system monitoring, evaluation frameworks, reliability engineering and model performance optimization.

• Demonstrated ability to design scalable, enterprise-grade AI architectures that integrate multiple models, services, and workflows.

• Previous experience working in a fast-paced startup or scale-up environment is highly desirable.

Benefits

• Salary: $200k - $275k

• Comprehensive benefits package.

Our client, a fast-growing venture-backed FinTech startup, is hiring a Software Engineer to join their team in California. The successful candidate will play a key role in shaping both product and engineering foundations, building new features and products at the intersection of deep learning, computer vision and payments infrastructure from the ground up.


Responsibilities

• Build and deliver core product features across the full stack.

• Develop Machine Learning-powered systems for fraud detection and card scanning.

• Improve frontend user experience and backend functionality.

• Design, implement and maintain databases and production infrastructure.

• Write practical Python scripts and rapid prototypes to support experimentation.

• Work closely with the CEO to shape product direction and strategy.

Skillset

• Product-focused engineer with a practical, problem-solving mindset and real-world impact focus.

• Broad technical capability across frontend, backend data, and infrastructure.

• Strong commitment to production-grade systems and high code quality.

• Proven ability to work independently in fast-paced startup environments.

• Strong bias toward shipping and iterating on user-facing features quickly.

• Interest or experience in deep learning and computer vision.

Benefits

• Salary: $130k.

• Equity.

Our client, an AI-driven startup within the manufacturing industry, is hiring a hands-on Director of AI to join their team in San Jose, CA. The successful candidate will play a key role in shaping the company's AI vision, developing the knowledge graph, agentic systems and machine learning infrastructure that drive intelligent decision-making across global manufacturing operations.


Responsibilities

• Lead the design, development and evolution of the company's AI and machine learning architecture.

• Build, deploy and scale production-grade knowledge graph systems that power intelligent decision-making.

• Develop advanced AI agents capable of reasoning across complex manufacturing, supply chain and operational datasets.

• Create intelligent planning, forecasting and decision-support solutions using real-time data.

• Collaborate closely with founders, engineers and customers to transform industry challenges into practical AI-powered products.

• Establish and maintain best practices for model development, deployment, evaluation, monitoring and governance.

• Support the growth of the AI function by helping to recruit, mentor and develop future AI and machine learning team members.

Skillset

• At least 6 years of experience in artificial intelligence, machine learning or applied research, with a strong record of delivering real-world impact.

• Master's or PhD in Computer Science, Artificial Intelligence, Machine Learning or similar.

• Demonstrate a proven ability to build, deploy and scale AI and machine learning systems in production environments.

• Have hands-on experience designing, implementing and managing knowledge graph solutions at scale.

• Possess deep expertise in agentic AI, reasoning frameworks, retrieval systems or multi-agent architectures.

• Show a strong understanding of modern machine learning infrastructure, MLOps practices and model lifecycle management.

• Communicate complex technical concepts clearly and effectively to both technical and non-technical stakeholders.

• Track record of building and scaling enterprise SaaS products and platforms is a plus.

• Exposure to manufacturing, supply chain or industrial technology environments is a bonus.

Benefits

• Salary: $160,000-$180,000

• Meaningful Equity.

• Flexible hybrid working.

Our client, an early-stage, AI-driven startup in the defense industry, is hiring an AI Researcher to join their team in California. The successful candidate will combine advanced machine learning research with robotics and defense applications, transforming foundational research into scalable, robust models that operate effectively in unstructured, high-stakes environments - from concept through to deployment.


Responsibilities

• Conduct original research in embodied AI, including reinforcement learning, imitation learning, memory, reward design, vision-language modeling and world modeling.

• Build, test and benchmark large-scale models for perception, decision-making and control in both simulated and physical environments.

• Investigate transfer learning and continual learning across diverse robotic domains.

• Collaborate with engineering, robotics and field teams to integrate research into operational systems.

• Lead research strategy and define the roadmap across key areas of autonomy and machine learning.

• Support field tests and data collection campaigns to evaluate system performance in realistic environments.

Skillset

• PhD in Computer Science, Robotics, Machine Learning or similar.

• Proven publication record in top-tier conferences or journals.

• Deep expertise in reinforcement learning, imitation learning, vision-language models, sim-to-real transfer, world modeling or agentic AI.

• Hands-on experience building and evaluating models for embodied agents or autonomous systems.

• Proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow or JAX.

• Experience working with large-scale datasets and high-dimensional sensor inputs.

• Demonstrated ability to take research ideas from concept to deployed prototype.

• Background in DoD, aerospace, or other mission-critical operational deployments is a plus.

• Legal authorization to work in the U.S.; some duties may require access to U.S. export-controlled information.

Benefits

• Salary: $160K - $220K DOE. Exceptional candidates may be considered for higher compensation.

• Performance Bonus.

• Equity.

• Medical, dental and vision insurance.

Our client, an early-stage AI startup, are hiring a Founding Applied AI Engineer to join their team in New York. The successful candidate will design and build the intelligence layer that powers the company's personalisation, recommendation systems and external APIs, including transforming behavioural data into meaningful, actionable understanding of users.


Responsibilities

• Partner with founders to identify which user signals (taste, behaviour, intent, identity) drive value.

• Translate ambiguous product questions into measurable modelling problems.

• Define what "user understanding" means in a data-driven system.

• Design and implement recommendation systems including collaborative filtering, matrix factorisation, embedding models and two-tower architectures.

• Build cross-domain recommendation systems across media and consumption types.

• Develop scalable systems that convert behavioural signals into actionable user representations.

• Create trait inference pipelines and behavioural feature systems.

• Design reusable user feature abstractions for downstream products and APIs.

• Design and run A/B tests, bandit systems and offline evaluation frameworks.

• Define what is stored, inferred and exposed via context APIs, and help shape how external systems consume user context safely and effectively.

Skillset

• Strong foundation in machine learning, particularly statistical modelling and feature engineering.

• Proven experience building production recommendation systems (e.g. collaborative filtering, matrix factorisation, embeddings).

• Experience working with large-scale behavioural or interaction datasets (ads, media, e-commerce or consumer platforms).

• Strong Python skills, with comfort in research-style environments such as Jupyter notebooks and experimentation codebases.

• Deep understanding of classical ML and recommender systems, with pre-LLM or hybrid systems experience strongly preferred.

• Experience designing and running A/B tests, bandit systems or other online experimentation frameworks.

• Ability to evaluate models using rigorous statistical methods and sound experimental design.

• Familiarity with modern ML frameworks such as PyTorch, JAX or equivalent tools.

• Strong product intuition, with a focus on user impact over purely model-centric metrics.

• Ability to operate in ambiguous problem spaces and translate technical outputs into product and business decisions.

Benefits

• Salary: $180k - $250k DOE.

Our client, an AI-driven HealthTech startup, are hiring a talented Forward Deployed Engineer to join the team in New York. The successful candidate will act as the link between the company's core technology and clinical partners, working directly with hospitals and healthcare networks to deploy, integrate and scale their real-time neural monitoring platform.


Responsibilities

• Work at the intersection of machine learning infrastructure and clinical systems, translating advanced neural monitoring technology into real-world hospital environments.

• Collaborate directly with hospitals and clinics to deploy and integrate their machine learning models and infrastructure.

• Design and implement integrations with hospital IT systems and EEG monitoring equipment.

• Troubleshoot complex infrastructure challenges, including secure networking, high-throughput data ingestion and low-latency inference in diverse clinical environments.

• Deliver reliable, scalable and secure deployments in mission-critical healthcare settings.

Skillset

• At least 3 years of experience in software engineering, infrastructure engineering or forward-deployed engineering roles.

• Strong proficiency in Python.

• Practical experience with containerisation and orchestration tools such as Docker and Kubernetes.

• Strong background in troubleshooting Linux environments, networking systems and secure deployment architectures.

• Excellent communication skills, with the ability to collaborate effectively across engineering teams and clinical or IT stakeholders.

• Strong ownership mindset, with the ability to work independently and willingness to travel to client sites when required.

• Experience working with healthcare technology, clinical data systems, or HIPAA-compliant infrastructure is a plus.

• Familiarity with real-time data pipelines or low-latency machine learning systems is a bonus.

• Exposure to medical device environments or hospital IT integrations is desirable.

Benefits

• Salary: $130k - $160k.