Machine Learning Engineer

We are seeking a highly skilled Machine Learning Engineer for a 6‑month contract to help build and advance a next‑generation recommendation engine. This solution will determine which financial products—such as mortgages, investment funds, and other offerings—should be presented to customers, optimizing for both relevance and highest potential revenue. You will play a hands‑on role in architecting and developing the model, leveraging an existing version‑one foundation that includes established data pipelines, engines, and cloud infrastructure. Your primary focus will be to design and build the recommendation system, while the MLOps team will support deployment, scaling, and long‑term maintenance.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.

Strong experience with general machine learning concepts, model development, and model evaluation
Hands‑on experience building recommendation systems
Proficiency in Python, SQL, and ML libraries such as TensorFlow and PyTorch
Demonstrated ability to develop scalable, production‑ready ML solutions
Experience working with cloud‑based data pipelines and existing ML infrastructure
Ability to design and execute ML experiments and bring models from concept to working prototype
Strong problem‑solving skills and ability to work independently in a fast‑paced environment

Experience with model deployment or working with MLOps teams
End‑to‑end ML lifecycle exposure—from data ingestion to monitoring
Hands‑on familiarity with AWS SageMaker
Deep knowledge of recommendation system algorithms and large‑scale personalization
Prior experience in financial services or fintech environments
Knowledge of cloud architecture best practices (AWS preferred)
Understanding of feature stores, vector search, or embedding‑based recommender approaches

Benefit packages for this role will start on the 1st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.