Build and maintain machine learning models and pipelines used in production
Contribute to data processing, feature engineering, model training, and evaluation workflows
Assist in deploying, monitoring, and validating ML models in production environments
Partner with senior engineers and product managers to implement ML-driven features
Write high-quality, well-tested code and help prevent regressions through testing and monitoring
Learn and apply best practices in ML engineering, system reliability, and scalability
Participate in design discussions, code reviews, and team knowledge sharing
Grow your technical skills in a fast-paced, high-impact environment

Requirements

3+ years of professional software engineering experience, with 2+ years working on machine learning or data-driven systems
Proficiency in Python and familiarity with ML frameworks such as PyTorch, TensorFlow, or xgboost
Experience with data analysis and processing tools such as pandas, SQL, Spark, or similar
Exposure to building or supporting ML pipelines for training, validation, or deployment
Understanding of production concerns such as monitoring, performance, and data quality
Strong collaboration and communication skills, with a growth-oriented mindset

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

machine learningdata processingfeature engineeringmodel trainingmodel evaluationPythonPyTorchTensorFlowxgboostSQL

collaborationcommunicationgrowth-oriented mindset