Sr Machine Learning Engineer

Top Requirements:

1. Mixed-Integer Programming (MIP)modeling; formulatingreal-world businessrules asdecision variables, linearconstraints, andobjectives; LP/IP theory; branch-and-bound intuition.
2. Commercial solverexperience; FICO Xpress (stronglypreferred) or Gurobi/CPLEX/OR-Tools/Hexaly, including solvertuning (gaps, threads, seeds, determinism) andreading solver logs/.lp files.
3. Programming to implement model & visualizemodel solutions; Java (themodellives inJava behind a solverabstraction); Python (incl. Streamlit for thedashboard); ableto code and ship changes in both programming languages.

Also required: comfortableusing AI coding agents(Claude/Copilot) for fastchanges; high codingstandards; a collaborative teamplayer (open toideas/feedback, no solo work);a fastlearner.

4. MSor PhD inOperations Research/ IndustrialEngineering /Applied Math (or related), plus3+years appliedoptimization or equivalentdemonstrated MIP experience.

(Education:MS/PhD in OR /IE /Applied Math /CS-optimizationor equivalent.)

Nice To Have:

Java21 / SpringBoot familiarity; clean/hexagonal model design (ports & adapters); TDD (JUnit5) foroptimizationmodels(LP-file integration tests); scheduling/assignment/routing problem experience; heuristics/metaheuristics/CP as complements toMIP; dataanalysis & debugging;mining datasets (incl. AzureADLS) andsolver logs to findissues and derive insights;data wrangling (CSV/Excel/SQL); Git/GitHub, MongoDB Compass, Maven,Docker; aviation / MRO domain.

Description:

Collaborate with leaders, business analysts, project managers, IT architects, technical leads and other engineers, along with internal customers, to understand requirements and develop needs according to business requirements for AI solutions

Maintain and enhance existing enterprise services, applications, and platforms using domain driven design and test-driven development

Troubleshoot and debug complex issues; identify and implement solutions

Create detailed project specifications, requirements, and estimates

Research and implement new AI technologies to enhance current processes, security, and performance

Work closely with data scientists and product teams to build and deploy machine learning models, focusing on the technical aspects of model deployment.

Implement and optimize Python-based ML pipelines for data preprocessing, model training, and deployment.

Monitor model performance and implement strategies for bias mitigation and explainability. Responsible for ensuring models are scalable and efficient in production environments.

Write and maintain code for model training and deployment, collaborating with software engineers to integrate models into applications.

Partner with a diverse team of experts, leveraging cutting-edge technologies to build scalable and impactful AI solutions.

Minimum Qualifications Education & Prior Job Experience

Bachelor's degree in Computer Science, Computer Engineering, Data Science, Information Systems (CIS/MIS), Engineering or related technical discipline, or equivalent experience/training

7 to 9+ years of full Software Development Life Cycle (SDLC) experience designing, developing, and implementing large-scale machine learning applications in hosted production environments

2+ years of professional, design, and open-source experience