AI/ML Engineer Jobs

Our client, an exciting Series B FinTech Startup, is hiring a Staff Machine Learning Engineer to join the team remotely. The successful candidate will design and deploy advanced machine learning models to help build interpretable, high-performing and scalable solutions leveraging data from AWS and Snowflake environments to drive impactful, data-informed decisions.


Responsibilities

• Designing, developing and deploying machine learning models to support predictive analytics across key fintech applications.

• Collaborating closely with cross-functional teams, including Data, Engineering and Product, to deliver integrated, data-driven solutions.

• Ensuring high model performance and reliability through robust data pipelines and scalable infrastructure.

• Converting model outputs into actionable insights that drive business strategy and financial inclusion outcomes.

• Mentoring and supporting fellow team members to promote a culture of technical excellence and collaboration.

• Championing best practices in MLOps, data governance and regulatory compliance across the ML lifecycle.

Skillset

• PhD or Master’s degree in Computer Science, Mathematics, Statistics or similar.

• 10+ years of relevant experience in applying AI/ML techniques within the financial services or fintech sectors.

• Extensive experience developing and deploying machine learning models for tasks such as classification, regression and forecasting.

• Strong programming proficiency in Python and SQL.

• Hands-on experience with AWS, particularly SageMaker and Bedrock, for model training, deployment and fine-tuning.

• Familiarity with model lifecycle tools like MLflow, SageMaker Model Registry or similar platforms.

• Practical experience using PyTorch, Scikit-learn and Generative AI models.

• Knowledge of Large Language Models (LLMs) and frameworks such as Hugging Face, LangChain or Mirascope.

• Solid understanding of cloud-based data architecture, including Snowflake, Amazon S3 and PostgreSQL.

• Background working in FinTech, PropTech or startup environments is a bonus.

Benefits

• Salary: $200,000 - $235,000.

• Equity.

• Remote working.

• Comprehensive health, dental, and vision insurance.

• 401(k).

Our client, an exciting HealthTech organization, are hiring an AI Engineer to join the team in New York. The successful candidate will lead the architecture, development and deployment of Agentic AI and production-grade LLM applications, as well as design intelligent, scalable and resilient AI-based systems that drive real impact, transforming clinical and scientific workflows.


Responsibilities

• Design and architect agentic AI systems that address complex, real-world problems with clarity and precision.

• Lead the development of advanced prompting strategies and drive prompt engineering for production use.

• Make strategic decisions on model selection, workflow orchestration and system optimization.

• Establish and promote best practices for AI system reliability, observability and performance.

• Develop and maintain LLM-powered applications using modern Python frameworks.

• Build robust, asynchronous task-handling systems leveraging technologies like SQS and Redis.

• Architect fault-tolerant systems to handle LLM unpredictability and service disruptions gracefully.

• Mentor and guide engineers on AI architecture, agentic design and production tooling.

• Lead the adoption of emerging AI frameworks and tools across the organization.

• Play a key role in defining the AI roadmap and shaping the long-term technical direction.

Skillset

• PhD in Computer Science, Machine Learning or similar with at least 5 years of experience building, deploying and scaling production-grade AI/ML applications.

• Proven expertise in advanced prompt engineering and deploying LLM workflows in production environments.

• In-depth knowledge of agentic AI patterns and orchestration frameworks.

• Hands-on experience managing LLM operations, including deployment, scaling and lifecycle management.

• Strong command of modern Python, including asyncio, FastAPI and related frameworks.

• Familiarity with agentic and LLM tools such as LangGraph, PydanticAI or equivalent.

• Experience working with leading foundation models, including Claude, GPT-4 and others.

• Solid understanding of distributed systems, asynchronous processing and queuing technologies (e.g. SQS, Redis).

• Deep interest in applying AI to solve real-world challenges in healthcare and life sciences.

• Excellent written and verbal communication skills, with the ability to convey complex ideas clearly.

Benefits

• Salary: $180k - $200k

• Bonus.

• Comprehensive benefits package.

• Design and fine-tune both open source and proprietary large language models (LLMs) for tasks including summarization, reasoning, planning and question answering.
• Build and enhance advanced Retrieval Augmented Generation (RAG) pipelines featuring embedding fine-tuning, hybrid search, reranking and knowledge graph integration.
• Develop autonomous AI agent workflows that support proactive and adaptive decision-making.
• Utilize reinforcement learning methods (such as PPO, DPO, GRPO) to continuously improve model performance.
• Create evaluation frameworks and define metrics to rigorously assess model effectiveness.
• Deploy AI models into production environments with a focus on low latency, reliability and scalability.
• Work closely with product and engineering teams to deliver comprehensive AI-powered financial solutions.

• Master’s or Bachelor’s degree with at least 5 years of professional experience in applied AI/ML engineering.
• Demonstrated success in delivering generative AI products utilizing LLMs and autonomous agent workflows.
• Practical expertise with LLM fine-tuning methods (such as LoRA), inference frameworks (including vLLM) and sophisticated RAG pipelines.
• In-depth understanding of reinforcement learning fine-tuning techniques and associated frameworks.
• Early-stage startup experience is an advantage.

• Salary: $190k - $225k DOE.
• Remote working.
• Comprehensive health, dental and vision coverage.
• Retirement benefits.

Our client, an exciting HealthTech company, are hiring a Senior Full Stack Engineer to join the team in New York. The successful candidate will play a key part in designing and building the backend systems that drive their AI-powered patient engagement platform, as well as lead engineering initiatives to create scalable infrastructure and deploy machine learning solutions that deliver real-time impact on patient outcomes.


Responsibilities

• Develop and maintain scalable backend services and APIs that support the AI-driven platform.

• Design and manage infrastructure for deploying and monitoring LLM-based applications.

• Partner with ML engineers to integrate conversational AI and predictive models.

• Lead the architecture of a flexible backend system that grows with data and product demands.

• Establish and manage CI/CD pipelines, automated testing and deployment processes.

• Write secure, efficient and maintainable code in line with engineering best practices.

• Create reusable components and libraries to streamline development workflows.

• Leverage cloud services (GCP, Azure, AWS) to build scalable and cost-effective infrastructure.

• Conduct code reviews and help define engineering standards.

• Identify, troubleshoot, and resolve system performance and reliability issues.

Skillset

• At least 5 years of experience in full stack development, with a minimum of 2 years in a senior engineering role.

• Proven ability to build early-stage products from concept to launch, and scale them successfully.

• Proficient in Node.js, Python, React, Express and relational database technologies.

• Practical experience or strong enthusiasm for integrating LLMs into production environments.

• Expertise in designing scalable and maintainable system architectures.

• Solid understanding of Clean Code principles, test-driven development (TDD), and CI/CD workflows.

• Familiarity with Docker, Kubernetes, and modern DevOps practices.

• Knowledge of AI/ML deployment workflows, A/B testing frameworks, and monitoring tools.

• Demonstrated leadership in driving engineering projects to successful delivery.

• Industry experience in healthcare technology is a bonus.

Benefits

• Salary: $160k - $175k

• Equity.

• Remote and flexible working options.

• Health, dental and retirement package.

• Lead research efforts in LLMs and VLMs, covering model development, evaluation, optimization and benchmarking.
• Shape the strategic direction of open-source AI/ML innovation within the organization’s  platform.
• Publish impactful research in leading academic venues.
• Build and nurture academic partnerships to strengthen the company’s global open research community.
• Mentor and guide team members, encouraging a culture rooted in scientific excellence and open collaboration.

• PhD degree in Computer Science or a related field, with a specialization in AI/ML.
• Proven track record of publications in leading AI/ML conferences and journals.
• Demonstrated leadership in driving research initiatives and managing complex technical projects.
• Expert-level proficiency in machine learning, with hands-on experience in PyTorch, LLMs and VLMs.
• Strong commitment to open source and a passion for building in the open through community collaboration.

• Salary: $160K–$220K DOE.
• Equity.
• Comprehensive health, dental and vision insurance.
• Hybrid working with offices in Seattle, WA and Palo Alto, CA.

Our client, a fast-growing healthcare organization, are hiring a Machine Learning Engineer to join the team in New York or San Francisco. The successful candidate will play a key role in shaping the future of conversational AI by driving meaningful improvements in patient outcomes and transforming the way healthcare systems engage and communicate.


Responsibilities

• Develop and implement machine learning models tailored for SMS and voice-enabled conversational AI.

• Create scalable pipelines to support data ingestion, model training and real-time deployment.

• Fine-tune large language models using healthcare-focused datasets to enhance accuracy and relevance.

• Collaborate with full-stack engineering teams to seamlessly integrate AI capabilities into core product experiences.

• Lead the full lifecycle of model deployment, including monitoring, troubleshooting and iterative optimization.

• Continuously explore emerging AI/ML technologies and healthcare innovations to keep their solutions cutting-edge.

 

Skillset

• At least 4 years of experience in AI/ML engineering, with a strong focus on NLP, large language models and conversational AI.

• Proven track record of deploying ML models into production, preferably within healthcare or other regulated industries.

• Proficient in Python and experienced with ML frameworks such as TensorFlow and PyTorch.

• Strong skills in fine-tuning LLMs, prompt engineering and integrating models into real-world applications.

• Comfortable working with cloud platforms (e.g. AWS, Azure, GCP) and knowledgeable in MLOps practices for scalable deployments.

• Experience with voice and speech-based technologies, including recognition and generation.

• Hands-on background in designing and implementing conversational AI solutions.

• Exceptional analytical and communication abilities.

• Familiarity with HIPAA compliance and handling of sensitive healthcare data is a bonus.

Benefits

• Competitive Salary.

• Equity.

• Remote working.

• Comprehensive healthcare package.