DATA & AI STAFFING AGENCY
MASSACHUSETTS

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Senior AI Engineer

Cambridge, MA – 4 days onsite

$200,000 – $220,000 + bonus + equity

THE COMPANY

Harnham is partnering with a well-funded biotech startup that is developing an AI-driven approach to more personalized cancer monitoring-integrating proprietary methods, diverse datasets, and evolving diagnostic capabilities to support ongoing care for individuals with elevated risk. The team brings experience across genomics and health data modeling, applying these foundations toward new screening and recommendation approaches, with a focus on translating research into practical clinical applications.

RESPONSIBILITIES

• Model Development & Deployment – Develop, train, and deploy ML models for biomarker detection, risk stratification, longitudinal monitoring, and decision-support systems for screening and survivorship.
• ML Infrastructure – Build and maintain scalable pipelines for data ingestion, feature engineering, training, and model serving on cloud platforms (e.g., AWS, GCP).
• Data Engineering – Collaborate with clinical and data teams to curate and manage high-quality, multi-modal datasets (e.g., genomics, imaging, EHRs).
• Research to Production – Turn advanced research into real-world systems, including adapting foundation models and integrating multi-modal learning into clinical workflows.
• Evaluation & Monitoring – Implement evaluation frameworks, experimentation pipelines, and monitoring tools to ensure robust, clinically reliable performance.
• Collaboration – Partner with clinicians, researchers, product managers, and engineers to align technical solutions with healthcare needs.

SKILLS AND EXPERIENCE

• MSc or PhD in computer science, machine learning, computational biology, or a related field
• Proven experience building and deploying ML models in production
• Strong Python skills and experience with frameworks like PyTorch, JAX, or TensorFlow
• Familiarity with cloud GPUs/TPUs, modern ML pipelines, and containerization (e.g., Docker)
• Solid software engineering practices (version control, testing, CI/CD, code review)
• Ability to communicate complex concepts to technical and non-technical audiences
• Experience with healthcare or biomedical data (e.g., genomics, pathology, EHRs)
• Publications or open-source contributions in relevant fields
• Startup or entrepreneurial experience, especially in fast-paced environments
• Experience building ML systems from zero to one

BENEFITS

The compensation package contains a base salary, bonus, equity and a comprehensive benefits package.

HOW TO APPLY

Please register your interest by sending your CV via the Apply link on this page.

KEY TERMS

Artificial Intelligence | AI | Deep Learning | Machine Learning | ML Engineer | Production | Real Time | Cancer Detection | Statistics | Reinforcement Learning | Foundation Modeling | Foundational Models | Anomaly Detection | Publications | Biotech | Health-tech | Genomics | Oncology | Pathology | EHR | Electronic Health Records | GPU | TPU | Startup | Engineering | End-to-end | Deployment | Container | Docker | CI/CD | CI / CD | Integration

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Senior Machine Learning Engineer

Location: Fully Remote (Hybrid option in NYC)
Compensation: $190,000-$200,000 + Equity
Type: Full-Time

About the Company
We are partnering with a fast-growing, profitable SaaS company that is redefining programmatic advertising through AI-driven solutions. Their platform empowers brands to deploy custom algorithms across major DSPs (The Trade Desk, DV360, Meta, YouTube), enabling smarter, real-time ad-buying decisions. Backed by leading industry investors, this company is building ML infrastructure and solving problems that don’t have off-the-shelf solutions.

Why Join?

• Work on distributed ML infrastructure using Ray + PyTorch on Databricks.
• Build solutions that create a new software layer in ad-tech.
• Flexible working hours, fully remote, and equity participation.
• Opportunity to grow into Principal ML Engineer later this year.

Role Overview

As a Senior Machine Learning Engineer, you’ll own the ML lifecycle end-to-end, focusing on productionization and robust MLOps practices. You’ll work closely with data science and engineering teams to deploy models at scale and build automation for training, inference, and observability.

Key Responsibilities

• Deploy ML models into production using CI/CD best practices.
• Monitor and manage ML drift; retrain models as needed.
• Build automation for ML lifecycle (training, inference, observability).
• Contribute to internal API development for future projects.
• Collaborate across teams to productionize models for client and internal use cases.

Must-Have Skills

• Strong experience with CI/CD (GitHub Actions, build automation, packaging).
• Expertise in MLOps (MLflow, model versioning, monitoring).
• Hands-on with Databricks (Delta Lake, Unity Catalog, Asset Bundles).
• Proficient in Python and PySpark.
• 3-6 years of relevant experience.

Nice-to-Have Skills

• Kubernetes and containerized environments.
• API development exposure.
• Distributed training (Ray) and observability tools (Prometheus, Grafana).
• Familiarity with embedding models and Databricks Clean Room.

Screening Process

1. Intro (with Director of ML or Senior Engineer) + short live coding exercise.
2. Take-home exercise (CI/CD-focused).
3. Final interview with leadership.
4. CEO check-in.

Interested?
Apply now to join a team building brand-new solutions in ad-tech and work with technologies like PyTorch, Ray, Databricks, and MLflow.

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This is an opportunity to work on real-world AI applications from concept through production, leveraging the latest advancements in large language models, conversational AI, retrieval systems, and intelligent automation. The ideal candidate is a hands-on builder with recent experience deploying production-grade GenAI solutions and thrives in a fast-paced, collaborative environment.

Responsibilities

• Design, prototype, and deploy Generative AI solutions across customer-facing and internal business applications.
• Develop and optimize applications powered by large language models (LLMs), vector databases, prompt engineering techniques, and Retrieval-Augmented Generation (RAG) architectures.
• Build, deploy, and maintain AI-powered chatbots and virtual assistants, ensuring scalability, reliability, security, and compliance.
• Lead the development of AI agents for both digital and voice-based experiences, supporting real-time interactions for customers and employees.
• Evaluate, integrate, and implement third-party AI platforms, APIs, and emerging technologies to accelerate innovation and business value.
• Create proof-of-concept applications to assess new use cases such as document processing, classification, summarization, knowledge management, and workflow automation.
• Optimize prompts, model configurations, and orchestration frameworks to improve performance, accuracy, and cost efficiency.
• Partner closely with data, platform, and MLOps teams to ensure robust deployment processes, monitoring, observability, and governance practices.
• Collaborate with product managers, engineers, and business stakeholders to translate user needs into scalable AI solutions.
• Contribute to architectural discussions and establish best practices for enterprise AI adoption and integration.

Qualifications

• Bachelor’s degree in Computer Science, Data Science, Statistics, Engineering, or a related technical field.
• 6+ years of experience in AI/ML engineering, software engineering, data engineering, or natural language processing, including recent hands-on work with Generative AI and LLM-based applications.
• Demonstrated success building and deploying production-grade AI chatbots, assistants, or conversational AI solutions within the last two years.

Required Skills

• Advanced Python programming skills and experience with modern AI frameworks and libraries such as LangChain, Hugging Face, OpenAI, Transformers, or similar technologies.
• Experience working with vector databases such as Pinecone, Weaviate, Chroma, FAISS, or equivalent platforms.
• Strong understanding of RAG architectures, prompt engineering, model evaluation, API orchestration, and LLM optimization techniques.
• Solid SQL skills and experience working with cloud-based data platforms and large-scale datasets.
• Ability to operate effectively in cross-functional teams and collaborate with product, engineering, analytics, and external partners.
• Strong communication skills with the ability to explain complex AI concepts and outcomes to both technical and non-technical audiences.

Preferred Qualifications

• Experience working in highly regulated industries such as financial services, healthcare, insurance, or telecommunications.
• Hands-on experience developing voice AI, speech-enabled assistants, or conversational systems integrated with telephony platforms.
• Familiarity with modern data stack technologies, including cloud data warehouses, transformation tools, and data orchestration frameworks.
• Experience integrating AI solutions with CRM, customer service, or workflow management platforms.
• Exposure to document intelligence use cases including OCR, information extraction, summarization, semantic search, and personalized recommendations.
• Experience supporting customer-facing applications, contact center technologies, or enterprise-scale service operations.

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Principal Machine Learning Engineer – ML Platform

REMOTE – US

$180,000-$230,000 + Equity

We’re partnered with a scaling AI‑driven technology company building large‑scale, production‑grade ML systems used in real‑time decisioning. They’re seeking a Senior Machine Learning Engineer who loves production ML over research, with an emphasis on distributed compute, reliability, and end‑to‑end ownership.

This is a role for someone who enjoys shaping platform architecture while still being hands‑on.

What you’ll be doing

• Designing, training, and deploying high‑scale ML models used in live systems
• Building distributed training pipelines (PyTorch, Ray)
• Owning the ML lifecycle across feature engineering, training, evaluation, inference, monitoring
• Improving ML reliability, observability, and reproducibility
• Working closely with engineering, SRE, and product to shape platform direction
• Contributing to ML architecture standards, CI/CD, and testing frameworks

What they’re looking for

• Strong experience delivering production ML systems end‑to‑end
• Expertise with Python, PyTorch, distributed compute (Ray, Spark)
• Background in large‑scale data processing and MLOps tooling
• Ability to diagnose production issues and drive architectural improvements
• Experience with event‑driven ML and model deployment frameworks is a plus

Why this role

• High ownership of ML platform direction
• Complex, real‑world ML workloads at meaningful scale
• Opportunity to improve and evolve existing infrastructure
• Equity + strong compensation package

HOW TO APPLY

If you’re passionate about building robust, scalable ML systems that drive real business impact, apply now.

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Forward Deployed Senior Data Scientist

Salary: $175,000+ (Depending on Experience)

Locations: Remote (with 25% travel)

THE COMPANY

A high‑growth, mission‑focused technology organisation is expanding its advanced analytics and AI function. Operating in a complex, data‑rich environment, the team builds scalable, high‑impact AI systems that support critical decision‑making and deliver tangible operational value. The environment is fast‑paced, innovative, and ideally suited to someone who thrives in high‑autonomy, high‑impact roles.

THE ROLE

As a Forward Deployed Senior Data Scientist, you will work directly with stakeholders to translate complex problems into deployable AI solutions. You’ll use a combination of proprietary and commercial datasets to uncover insights, build models, and deploy production‑ready systems that support strategic decision‑making.

This role blends hands‑on data science, AI engineering, rapid prototyping, and end‑to‑end delivery ideal for someone who is highly analytical, scrappy, and passionate about solving complex technical challenges with real‑world impact.

KEY RESPONSIBILITIES

• Build advanced AI/ML/DS models and systems tailored to high‑value operational challenges
• Develop new AI‑driven technology stacks designed for specific customer use cases
• Lead end‑to‑end delivery of AI projects, from scoping to production deployment
• Partner with research, engineering, and software teams to deliver robust AI products
• Define architectural standards and project roadmaps for scalable AI systems
• Create evaluation frameworks for AI deployments, including performance, reliability, and observability
• Mentor junior team members and help shape a culture of excellence and innovation
• Stay current with emerging techniques in AI, LLMs, and agentic systems; drive adoption of best practices
• Build agentic AI systems leveraging reasoning frameworks and orchestrators
• Act as a technical leader, translating high‑level objectives into actionable technical plans

EXPERIENCE REQUIRED

• Extensive experience designing, developing, and delivering AI/ML solutions end‑to‑end
• Strong software and data science fundamentals (Python essential)
• Experience building production‑grade AI systems and integrating them into customer environments
• Ability to collaborate across research, engineering, and product teams
• Experience working with large‑scale datasets and cloud‑based ML deployments
• Strong organisational skills and the ability to communicate complex ideas clearly
• Proven ability to operate independently in fast‑moving environments and manage competing priorities
• Passion for rapid prototyping, experimentation, and building high‑impact solutions

DESIRABLE EXPERIENCE

• Publications in top AI/ML/NLP or decision science venues
• Experience developing evaluation systems for LLMs or agentic models
• Experience with fine‑tuning, post‑training, or advanced model adaptation
• Familiarity with MLOps, monitoring, deployment, and large‑scale model management
• Track record of converting research prototypes into production systems

THE OFFER

• Competitive compensation (around $175,000 base depending on experience)
• Opportunity to work on deeply impactful, high‑scale AI challenges
• High degree of autonomy, technical ownership, and end‑to‑end influence
• A fast‑paced, innovation‑driven environment with strong technical peers
• Exposure to cutting‑edge modelling, LLMs, and agentic system development

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Senior Machine Learning Engineer
Fully Remote, United States | $200,000 to $230,000 base plus equity and benefits

This is a high impact opportunity to shape how Vision Language Models are applied in real world, production grade systems. You will play a central role in building and scaling VLM driven intelligence that connects edge devices with cloud based reasoning, influencing both technical direction and product outcomes in a fast moving environment.

The Company
They are a technology led organisation building intelligent, connected solutions that blend advanced machine learning with real world operational workflows. Their platform is designed to turn complex visual data into actionable insights at scale. The team brings together expertise across machine learning, computer vision, embedded systems and data science, with a strong focus on building systems that perform reliably in production.

The Role

• Own the design and development of cloud based Vision Language Model pipelines used for large scale labelling and annotation
• Drive decisions on what visual signals, metadata and contextual information are captured from edge devices to maximise VLM performance
• Build and evaluate end to end inference systems, including prompt design, fine tuning strategies and model benchmarking
• Partner closely with embedded systems, computer vision and data science teams to close the loop between devices and cloud intelligence
• Stay at the forefront of the VLM landscape, assessing and integrating commercial and open source models as capabilities evolve

Your Skills and Experience

• Strong commercial experience as a machine learning engineer working with computer vision, LLMs or Vision Language Models
• Hands on experience evaluating, fine tuning or deploying VLMs in production environments
• Deep understanding of how edge constraints such as bandwidth, latency and compute influence model design
• Proficiency with Python, PyTorch and modern cloud based inference and evaluation tooling
• Practical expertise in prompt engineering and model evaluation, with a focus on measurable performance improvements
• Comfortable owning problems end to end and collaborating across hardware and software teams

What They Offer

• Competitive base salary of $200,000 to $230,000 plus equity
• Fully remote working across the United States
• Comprehensive benefits including medical, dental and vision cover
• Flexible paid time off and a strong culture of autonomy and trust
• The opportunity to be a technical leader in the application of Vision Language Models at scale

How to Apply
If you are excited by the challenge of building production grade VLM systems with real world impact, apply now to learn more about this opportunity.

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Principal Data Scientist – GenAI & Personalization

Remote (US) | $190k-$220k + 15% bonus

My client is a large, mission-driven learning technology organization reinventing itself as an AI‑first platform. Generative AI, personalization, and data science are now at the core of how millions of students learn – and they’re hiring a Principal Data Scientist to lead from the front.

This is a true hands-on principal IC role: deep technical ownership, real influence, no line management.

Why this role stands out

• Own and shape a core AI capability – scope built around your strengths
• Work on customer-facing GenAI products used at massive scale
• Strong leadership air cover – minimal meetings, protected focus time
• High-visibility work with real-world impact in education

What you’ll do

• Design and build GenAI systems that translate education standards into structured learning objectives
• Improve AI-driven assessments, content generation, and personalization engines
• Apply rigorous statistics to messy human data – and make it production-ready
• Partner closely with engineering on deployment, testing, and optimization

What they’re looking for

• PhD in Statistics or a highly quantitative field
• Strong generative AI experience (personalization or content generation a big plus)
• Excellent Python and end-to-end ownership – research → production → impact
• Clear communicator who can influence both technical and non-technical teams
• 4-5 years post-PhD industry experience

Bonus points for: MLOps, AWS/Databricks, or education experience (not required)

Logistics

• Fully remote (US-based)
• US Citizen or Green Card only (no sponsorship)
• Core availability: 11am-5pm EST

If you want principal-level ownership, meaningful scale, and the chance to define how GenAI shows up in real learning products – this role is built for that.

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