Machine Learning Engineer Jobs

Our client, a leading Health Insurance organization, is hiring a Software Engineer to join the team remotely. The successful candidate will work hand-in-hand with their product team to develop AI-driven features that transform how HR teams and employees engage with benefits and healthcare systems, while also equipping the company’s internal consulting teams with smarter, more efficient tools.


Responsibilities

• Partner with Product, Engineering and Design teams to uncover challenges and craft generative AI solutions using best-in-class software engineering practices.

• Integrate AI capabilities across the full stack (frontend, backend and infrastructure) seamlessly within their applications.

• Develop intelligent search and retrieval systems that help users find the information they need, faster.

• Design and optimise interactions with foundation models (GPT-4, Claude, Gemini) to deliver consistent and reliable results.

• Deliver AI-powered features with the same high standards of reliability, scalability and performance as all applications.

Skillset

• At least 5 years of experience building modern full-stack web applications using Python and JavaScript/TypeScript.

• Hands-on experience integrating foundation models directly via APIs to create intelligent applications.

• Proven ability to translate user needs into technical solutions while collaborating across cross-functional teams.

• Comfortable working across frontend, backend and infrastructure layers.

• Experience with advanced AI tools, including tool-calling, multi-agent systems and emerging AI capabilities.

• Machine Learning background, with experience in PyTorch, scikit-learn, and deploying proprietary or open-source models.

• Strong communicator capable of partnering effectively with non-technical stakeholders.

Benefits

• Salary: $150k - $200k DOE

• Stock options.

• Health, Dental and Vision insurance.

• Remote working.

Our client, an innovator in the financial services industry, is hiring a Staff Machine Learning Engineer to join their team remotely. The successful candidate will leverage their expertise in data science and ML operations to enhance model accuracy while optimizing infrastructure for both scalability and cost efficiency.


Responsibilities

• Enhance their pricing model to boost accuracy for high-value cards while minimizing infrastructure costs.
• Refine our underwriting model to optimize cash advance disbursements while keeping risk and default rates in check.
• Own the full ML lifecycle, from model training and feature engineering to deployment and monitoring.
• Work closely with pricing experts to gain deep domain knowledge of the trading card market and drive model improvements.
• Plan and run experiments and back tests to identify and validate features that strengthen predictive performance.
• Manage AWS infrastructure and develop code for our pricing API to ensure scalable, low-latency model delivery.

Skillset

• Minimum of 10 years of engineering experience, including at least four years focused on machine learning.
• Deep expertise in Python, with hands-on experience in libraries such as scikit-learn, XGBoost and pandas.
• Strong ML Ops and infrastructure background, with experience deploying models on AWS using ECS and Docker.
• Skilled in data orchestration and workflow management using Airflow for model training and batch processing.
• Demonstrated success improving model accuracy through feature engineering and experimentation.
• Experience with Random Forest, ensemble methods, or pricing/underwriting models in marketplace or fintech environments.

Benefits

• Salary: Circa. $250k.
• Equity.
• Remote working.
• 401(k) retirement benefits.
• Competitive healthcare package.

Our client, a leading innovator in Insurance industry, are hiring an AI Engineer to join their growing team in New York. The successful candidate will play a key role in executing the company’s AI strategy, along with designing, building and integrating intelligent, reliable and scalable AI-driven features into their core applications using modern web frameworks and cloud infrastructure.


Responsibilities

• Partner with product, engineering and design teams to uncover user challenges and deliver generative AI solutions using modern software development practices.

• Build end-to-end AI integrations across the full stack - frontend, backend and infrastructure - embedding intelligence directly into applications.

• Create smart search and information retrieval systems that enable users to access relevant data quickly and efficiently.

• Design and implement robust interactions with foundation models (e.g. GPT-4, Claude, Gemini) to ensure reliable and consistent performance.

• Deliver AI-powered features that uphold the highest standards of scalability, security and performance.

Skillset

• Minimum of 5 years of experience building modern full-stack web applications with Python and JavaScript/TypeScript.

• Practical experience integrating foundation models via direct API connections.

• Demonstrated ability to translate user challenges into elegant technical solutions and lead initiatives that deliver engaging AI experiences.

• Proficient across the full application stack, from frontend to backend and infrastructure.

• Knowledge of tool calling, multi-agent systems, and emerging frameworks such as Model Context Protocol (MCPs).

• Hands-on experience with Machine Learning (PyTorch, scikit-learn) and deploying proprietary or open-source models.

• Strong communication skills with a proven ability to collaborate effectively with cross-functional teams.

Benefits

• Salary: $170k - $200k

• Stock options.

• Healthcare, vision and dental insurance.

Our client, an innovator in the healthcare industry, is hiring a hands-on Tech Lead Manager (Machine Learning) to join their team in Utah. The successful candidate will lead the development of the Personalization Engine, combining hands-on machine learning engineering with team leadership to build and scale production ML systems that deliver real-world impact.


Responsibilities

• Take ownership of the machine learning system that powers the organization’s Personalization Engine.

• Lead the end-to-end ML lifecycle, including model development, deployment, monitoring and optimization.

• Ensure the platform remains reliable and scalable across millions of healthcare transactions.

• Build advanced ML solutions such as ensemble models, reinforcement learning approaches and multi-armed bandit systems.

• Architect and maintain high-performance MLOps infrastructure, including feature stores, data pipelines and monitoring systems.

• Strengthen feedback loops so models continuously learn and improve based on real patient behaviour.

• Lead, manage and mentor a team of machine learning engineers.

• Carry out thorough code and system design reviews to uphold strong technical standards.

• Promote a culture focused on experimentation, continuous learning and meaningful impact.

• Partner closely with product and design teams to translate complex patient journey challenges into ML-powered solutions.

Skillset

• At least 6 years of experience designing and deploying machine learning systems in production environments at scale.

• Proven experience building personalisation or recommendation engines for consumer-facing products (e.g. fintech, e-commerce).

• Strong programming capabilities in Python and SQL.

• Minimum of 2 years’ experience leading teams, managing engineers or operating as a technical ML lead.

• Hands-on experience across the entire ML lifecycle, including data pipelines, model development and MLOps.

• Ability to translate business challenges into practical machine learning solutions.

• Experience incorporating Generative AI into personalisation platforms or features is a bonus.

• Broader product engineering leadership experience beyond ML-focused systems.

Benefits

• Salary: $195,000 - $245,000 DOE.

• Equity.

• Flexible and Remote working options.

• Health benefits.

• 401(k) with 100% match up to 3%

Staff Machine Learning Engineer
Location: Remote

Are you tired of being kept in a restricted creative box with limited autonomy to push boundaries and ideas to solve problems with ML? 

Or not seeing your work directly impact the companies mission? 

If so , my HealthTech client is looking for a Staff ML Engineer who will love being in an autonomous environment where you will be given a problem area but full autonomy to be creative, push new ideas and build the ML solutions you feel is best. 

You'll join a smart and curious team who like to be challenged working on areas like Recommender Systems, LLMs & NLP, Timeseries and MLOps.

You'll achieve success here by combining your technical ML/AI end-to-end building skills with high positive energy and clear articulate communication skills. 

What else is in it for you? 

• Base Salary from 210-260k 
• Equity/Stocks

What do you need to be successful? 

• Are a technical leader who can work and manage their own projects and solutions with full autonomy. Like a Staff/ Principal ML Engineer / Scientist
• You can clearly articulate your thoughts and write and communicate them clearly.
• Build ML/AI solutions end to end in the ML Lifecycle from research to production
• Comfortable with being challenged and taking feedback to build better solutions with the right outcomes
• Can move with speed and intent and comfortable with life building a startup/scaleup

Interested? Click the apply or For more info reach out at anthonyh@alldus.com

Our client, an AI-driven organization impacting the ecommerce market, is hiring an experienced AI/ML Engineer to join their team in Los Angeles, California. The successful candidate will lead the design and implementation of AI verification pipelines, develop robust evaluation systems and deliver production-ready features impacting millions of users.


Responsibilities

• Lead the architecture and implementation of AI verification pipelines to ensure robust, reliable model performance.

• Design, build and maintain evaluation infrastructure for AI systems at scale.

• Develop production-ready AI features that are deployed to millions of users.

• Create reasoning systems that convert probabilistic AI outputs into deterministic, auditable recommendations.

• Collaborate with cross-functional teams to integrate AI-native products into broader platforms.

• Continuously monitor, test and improve AI systems to maintain performance, security and reliability.

Skillset

• Deep expertise in machine learning, AI verification and evaluation frameworks.

• Strong experience with probabilistic modeling, reasoning systems and knowledge graphs.

• Proficiency in Python and modern ML/AI libraries (e.g. TensorFlow, PyTorch, JAX).

• Experience building production-scale AI systems that serve millions of users.

• Strong understanding of software engineering principles: version control, CI/CD, testing, and deployment.

• Familiarity with adversarial testing, verification pipelines, and AI auditing.

• Experience in AI-native product design and implementation.

• Knowledge of cloud platforms (AWS, GCP, or Azure) for scalable AI infrastructure.

• Research experience in AI interpretability, explainability or safety is a bonus.

Benefits

• Salary: $350k - $450k DOE.

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 Facilities Management startup, is hiring a hands-on Head of Engineering to join their team in New York. The successful candidate will help define technical strategy and direction, while building the right systems and team to support the company as it scales.


Responsibilities

• Architect and own core, foundational AI and machine learning systems.

• Act as a strategic technical leader, shaping how AI is leveraged across the product and organization.

• Partner closely with founders and engineering leadership on long-term technical direction and key architectural decisions.

• Remain hands-on where necessary, particularly in the early stages, without operating permanently in an individual contributor role.

• Help define engineering standards, best practices and what “good” looks like as the company scales.

Skillset

• Early-stage startup experience is essential, such as a founding engineer, first AI hire or similar.

• Proven ability to wear many hats, combined with experience at a company that successfully scaled.

• Strong technical depth with clear fundamentals across AI and machine learning.

• Comfortable operating in ambiguous environments and building systems from zero.

Benefits

• Salary: $200k - $300k DOE.

Our client, a growing healthcare organization, is hiring a Product Manager to join their team in New York. The successful candidate will be responsible for shaping and delivering products that improve patient outcome, including taking full ownership of the product roadmap across the company’s core software platform and agentic workflows.


Responsibilities

• Own and deliver the product roadmap across the organization’s core platform and agentic workflows.

• Use structured prioritization frameworks to align business goals with client and patient needs.

• Drive the scaling of agentic systems to support increasing patient volumes and more complex interactions.

• Establish quality metrics, design experiments and continuously improve system performance.

• Lead market research and user discovery to identify unmet customer and patient needs.

• Prototype, test and validate new features quickly using an MVP-first approach.

• Act as the central liaison between technical teams (Engineering, Machine Learning) and business teams (Operations, Sales, Marketing).

• Translate product requirements into clear deliverables and ensure high-quality execution from ideation through launch.

Skillset

• At least 4 years of experience in product management roles.

• Minimum of 2 years delivering AI-native or agentic products into production.

• High-impact professional backgrounds in Investment Banking, Private Equity or Management Consulting will be considered.

• Demonstrated success scaling AI or data-driven products across growing user bases, data volumes and interaction complexity.

• Strong understanding of agentic system architectures and underlying technical principles.

• Proven ability to partner closely with engineering teams to build and scale complex data products.

• Strong analytical capabilities, including defining KPIs and using data to inform product decisions.

• Excellent communication skills, with ability to clearly explain complex technical concepts to non-technical stakeholders.

• Experience building and scaling products from 0 to 1 in fast-paced environments.

Benefits

• Salary: $160k - $185k

• Equity.

• Comprehensive health and dental benefits.

Staff MLOps Engineer
Remote

My client is a HealthTech startup helping individuals get healthier!
Sitting at the intersection of machine learning, infrastructure, and production systems. You'll get to build solutions across ML infra and MLOps that help drive velocity in Machine Learning to ship ML products quickly and safely.

You'll have autonomy and ownership to create, innovate and build solutions for the future of ML at the company creating huge impact.

You'll also get to build feature stores, test new MLOps tools, Optimize GPUs, inference and more. 


What else do you get? 

• Base Salary: 220-270k 

• Equity

• Fully Remote

What do you need to be successful? 

• Experience building solutions that drive ML product build velocity for the last 5+ years like ML Platform, ML Infra and MLOps. 

• Experienced with areas like real-time inferencing, GPU optimization, Feature store builds and over all ML lifecycle. 
• Worked with Cloud tools (GCP preferred or open to learning)

Interested in learning more? Apply or reach out to me at anthonyh@alldus.com

*Please note due to limited resources we are currently only shorlisting those who can work without visa support like Green Crad or Citizenship. 

Our client, a fast-growing AI startup, is hiring an AI/ML Engineer to join their team in New York. The successful candidate will focus on building the core Copilot product, with ownership across the full ML lifecycle - from data pipelines and model training to embeddings, retrieval, serving and continuous iteration in production.


Responsibilities

• Design, develop and deploy production-grade Machine Learning systems in Python, moving well beyond experimentation and notebooks.

• Take ownership of key components of the NLP and LLM stack, including embeddings, retrieval pipelines, RAG architectures and targeted fine-tuning.

• Build and iterate on recommendation and ranking models that surface who users should engage with and when.

• Work hands-on with vector databases and similarity search to drive relationship intelligence.

• Implement and maintain ML tooling for training, versioning, monitoring and evaluation.

• Collaborate closely with founders, product and engineering to translate ideas into shipped, measurable product capabilities.

• Integrate ML models into production APIs within a TypeScript / Nest.js–heavy environment.

• Continuously optimise latency, cost and performance, including model routing, caching, distillation and quantisation.

Skillset

• Minimum of 3 years of experience building and deploying production ML systems using Python, PyTorch or TensorFlow and scikit-learn.

• Hands-on NLP and LLM experience, including HuggingFace Transformers, embeddings, sentence-transformers and RAG architectures.

• Experience working with both proprietary models (e.g. OpenAI) and open-source LLMs (e.g. Llama, Mistral).

• Strong foundation in classical machine learning, including classification, ranking, supervised and unsupervised learning, and XGBoost or LightGBM.

• Experience with MLOps and infrastructure, such as experiment tracking, model versioning, Docker/Kubernetes, SageMaker or similar systems.

• Practical experience with vector databases, including Pinecone, Qdrant, Weaviate or comparable platforms.

• Strong software engineering fundamentals, with experience integrating ML models into reliable, production-grade systems.

Benefits

• Salary: Circa $250k.

• Equity.

• Health, dental and vision insurance.

Our client, an AI-driven organization within the Healthcare industry, is hiring a Staff Data Software Engineer to join their team in New York. The successful candidate will design, build and scale the data infrastructure that underpins agent improvement, clinical analytics and research collaboration. You will own streaming and batch pipelines to process agent conversations, clinical events and patient outcomes at scale.


Responsibilities

• Build and operate streaming and batch data pipelines on Databricks using Spark and Delta Lake.

• Design, implement and maintain CDC (Change Data Capture) pipelines that sync operational databases into Delta Lake.

• Develop data mining pipelines for persona discovery, scenario extraction and edge-case detection.

• Build and own the data backend for the Research Platform, including natural-language-to-SQL capabilities.

• Implement robust data quality checks, staleness detection and automated alerting.

• Develop pipelines for voice and SMS analytics, including call quality and engagement metrics.

• Support multi-region data deployments and compliance requirements.

• Collaborate closely with agent engineers and data scientists to surface insights that improve agent performance.

Skillset

• At least 4 years of experience in production data engineering roles.

• Deep, hands-on experience with Databricks, Spark and Delta Lake.

• Strong proficiency in Python and SQL for building and maintaining data pipelines.

• Experience designing and operating streaming pipelines and CDC (change data capture) systems.

• A solid understanding of data modelling, medallion architectures (bronze/silver/gold) and query optimisation.

• Experience implementing data quality frameworks, monitoring and alerting.

• A proven track record of delivering reliable, production-grade data infrastructure.

• Exposure to machine learning pipelines, including feature engineering and training infrastructure is desirable.

• Experience building natural-language query interfaces or LLM-powered data tools is a bonus.

• Experience working with healthcare data and familiarity with HIPAA compliance requirements is a plus.

Benefits

• Salary: $220k - $260k

• Health, dental and vision coverage.

• Mental Health and Wellness support.

Our client, a cutting-edge AI company revolutionizing software development, is hiring a Senior Software Engineer, AI Platform to join their team in New York. The successful candidate will contribute to designing and building the next-generation real-time layer for executing, deploying, governing and auditing AI applications, workflows and agents.


Responsibilities

• Develop, implement and fine-tune enterprise-level AI models and reliable production workflows.
• Create and maintain a real-time distributed execution engine that supports AI applications, agents and workflows.
• Design scalable and resilient systems that enable multi-tenant and hybrid cloud deployments, featuring secure APIs and a versatile integrations platform.
• Work closely with customers and design partners to collect feedback, validate approaches and guide product development.
• Collaborate with the product team to shape the roadmap and keep pace with the latest advancements in AI infrastructure.

Skillset

• At least 5 years of experience deploying and managing production applications in cloud environments.
• Extensive knowledge of containers, virtual machines, caches, task queues, networking and operating systems.
• Proven experience in building and running production AI systems.
• Familiarity with AI inference methodologies.
• Proficient with machine learning frameworks such as PyTorch and TensorFlow.
• Strong product intuition with a commitment to delivering smooth and intuitive user experiences.
• Strategic thinker who can anticipate market demands and develop effective technical solutions.
• Startup mindset - quick to act, comfortable with uncertainty, and passionate about turning ideas into delivered products.

Benefits

• Salary: $170K - $210k
• Equity
• Remote working within the U.S.

Our client, an AI-driven organization in the Fintech industry, are hiring a Staff Machine Learning Engineer to join the team in Colorado. The successful candidate will will focus on building end-to-end generative AI products leveraging your deep expertise in large language models, fine-tuning techniques and reinforcement learning.


Responsibilities

• Design and build multi-agent systems that automate tasks and streamline workflows, delivering measurable operational impact.

• Develop AI co-pilots for advisors and other user personas, supporting workflows across prospecting, conversion, onboarding and client servicing.

• Create purpose-built, low-latency models for complex, multi-turn financial services interactions.

• Enable AI-driven optimisation and navigation of legacy platforms using computer-use and automation models.

• Design, fine-tune, and deploy open-source and proprietary LLMs for use cases including Q&A, summarisation, reasoning and planning.

• Build advanced Retrieval-Augmented Generation (RAG) pipelines, incorporating query rewriting, embedding fine-tuning, hybrid search, re-ranking and knowledge graphs.

• Apply reinforcement learning techniques, including RL fine-tuning methods such as PPO, DPO, and GRPO, to continuously improve model performance.

• Deploy models to production, ensuring high performance, reliability, scalability and low latency.

Skillset

• At least 5 years of experience in applied AI/ML engineering.

• Demonstrated success delivering production-grade generative AI products with large language models at their core.

• Hands-on experience with LLM fine-tuning techniques (e.g. LoRA), inference frameworks (e.g. vLLM) and advanced Retrieval-Augmented Generation (RAG) architectures.

• Strong practical expertise in reinforcement learning fine-tuning methods and supporting tooling.

• Previous experience working in an early-stage startup is a plus.

Benefits

• Salary: $170k - $220k DOE

Our client, a FinTech innovator, are hiring a Staff Machine Learning Engineer with expertise in Large Language Models (LLMs) to join the team remotely. The successful candidate will be responsible for building Generative AI and LLMs solutions in a in a fast paced environment that will help transform financial advice delivery.


Responsibilities

• Lead the development and customization of large language models tailored for financial use cases.

• Apply cutting-edge tuning methodologies to enhance performance across conversational AI, content generation and strategic reasoning tasks.

• Create intelligent retrieval systems that combine multiple search approaches, semantic understanding and ranking mechanisms to deliver contextually relevant information at scale.

• Engineer autonomous AI systems capable of independent decision-making, integrating feedback loops and adaptive learning techniques to continuously enhance agent capabilities.

• Establish comprehensive testing and monitoring frameworks while overseeing production deployments that maintain high-performance standards under real-world conditions.

• Work closely with cross-functional teams to transform AI research into market-ready features that solve genuine business challenges.

Skillset

• Minimum 5 years of professional experience applying machine learning in commercial settings post-graduation.

• Must have at least 2 years’ experience working with LLMs and finetuning like QLORA / LORA and building RAG systems.

• Demonstrable success delivering end to end ML /AI products where generative AI drives core functionality, with particular emphasis on systems that exhibit autonomous behavior patterns.

Benefits

• Salary: $190,000 - $225,000 .

• Equity.

• Comprehensive health/dental/vision coverage.

• Retirement plans.

If interested hit apply below or reach out to me at joseph.mcdermott@alldus.com