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.

Your Role

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 operationalized models

Stay current on emerging ML and GenAI trends and apply them to practical, high-impact use cases

Required Qualifications

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, LangChain, Scikit-learn, and Pandas

Solid understanding of core ML and LLM concepts including transformers, embeddings, retrieval, evaluation, and optimization

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, GitHub Actions, or containerized workflows

Quantitative degree in Computer Science, Engineering, Math, Physics, or a related field (advanced degrees welcome but not required)

Preferred Qualifications

Contributions to open-source projects in ML, GenAI, or developer tooling

Public GitHub repositories or other visible examples of applied ML work

What Excites You

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

Compensation & Benefits

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