Machine Learning Engineer

Job Overview

We’re hiring a full‑time Machine Learning Engineer to join an AI technology company in the financial services space. The client builds advanced AI solutions that help financial institutions make smarter, fairer lending decisions across underwriting, fraud detection, and lending intelligence. Their platform supports hundreds of production AI models and focuses on scalability, explainability, and real‑world impact.

This role is ideal for engineers who enjoy bridging research and production, taking ownership of complex ML systems, and working closely with cross‑functional partners to turn cutting‑edge ideas into reliable, customer‑facing solutions.

Hybrid or remote in Boston, MA.

• Collaborate on end‑to‑end development of ML/AI‑powered systems, from ideation through production deployment
• Design and prototype experiments using modern ML and GenAI techniques to advance internal tooling and customer‑facing capabilities
• Partner cross‑functionally with product, data science, and go‑to‑market teams to align ML solutions with business needs
• Build internal frameworks and tooling that connect analytics platforms with ope rationalised models
• Stay current on emerging ML and GenAI trends and apply them to practical, high‑impact use cases

• 3 years of hands‑on, post‑graduation experience building and deploying production ML systems
• Strong Python expertise with the ability to build scalable, reliable services and tools
• Experience with ML and GenAI frameworks such as PyTorch, Hugging Face, Lang Chain, Scikit‑learn, and Pandas
• Solid understanding of core ML and LLM concepts including transformers, embeddings, retrieval, evaluation, and optimisation
• Familiarity with modern software engineering practices including testing, CI/CD, version control, and code reviews
• Ability to write efficient, resource‑aware code across CPU/GPU, memory, and I/O constraints
• Experience with automation and tooling such as Airflow, Git Hub Actions, or containerised workflows
• Quantitative degree in Computer Science, Engineering, Math, Physics, or a related field (advanced degrees welcome but not required)

• Contributions to open‑source projects in ML, GenAI, or developer tooling
• Public Git Hub repositories or other visible examples of applied ML work

• Designing and deploying GenAI‑powered tools that help teams and customers work more effectively
• Building platforms that make ML development faster and more accessible
• Translating research ideas into production‑grade systems
• Continuously learning and experimenting with new ML approaches
• Solving real‑world problems with measurable impact

• Competitive compensation with annual bonus eligibility
• Comprehensive medical, dental, and vision coverage
• 401(k) with generous employer match
• Unlimited vacation and paid company holidays
• Family leave, wellness, phone, internet, and professional development allowances