Job Description
Job Description
Machine Learning Engineer
Location : St. Louis, Missouri
Employment Type : Full-time, Direct Hire
Citizenship Requirement : Must be a U.S. Citizen
Salary Range : $112,000 – $145,000
About the Role :
You’ll design, develop, and deploy machine learning models to solve real-world business challenges. You will collaborate with data engineers, software developers, and product managers to integrate intelligence at scale. This role provides strong career growth in an emerging tech environment.
Key Responsibilities :
- Develop and train ML models (e.g., regression, classification, recommendation systems)
- Feature engineering and data preprocessing using structured / unstructured data
- Build and maintain production-quality ML pipelines (e.g., ETL, model serialization, API deployment)
- Analyze model performance, tune hyperparameters, and iterate to improve outcomes
- Integrate models into software systems or cloud-based platforms
- Collaborate with cross-functional teams to align ML deliverables with business objectives
- Maintain thorough documentation and stay current with latest ML methodologies
Required Qualifications :
Education : Bachelor’s degree (minimum) in Computer Science, Data Science, Information Technology, or related fieldExperience : 1–3 years applying ML in professional settings—internships and co-ops countCitizenship : U.S. Citizen (required)Technical Proficiency :Programming in Python (or Java / C++)Familiarity with ML libraries : scikit-learn, TensorFlow, PyTorch, or XGBoostExperience with data pipelines / tools : Spark, Airflow, or PandasKnowledge of model deployment (e.g., REST APIs, AWS SageMaker, Docker)Sound understanding of data structures, algorithms, and software engineering fundamentalsAnalytical Skills :The ability to analyze large datasets and extract insightsStrong problem-solving and debugging capabilitiesSoft Skills :Excellent teamwork and written / verbal communicationSelf-driven, with a mindset to learn and adapt rapidlyStrong attention to quality, documentation, and best practicesPreferred Qualifications :
Master’s degree in a quantitative disciplineExperience with deep learning frameworks (TensorFlow, PyTorch)Familiarity with MLOps platforms (MLflow, Kubeflow)Exposure to cloud environments (AWS, GCP, Azure)Understanding of big-data ecosystems (Hadoop, Kafka)What You’ll Gain :
A competitive base salary ($112–145K)Opportunity to work on real-world ML systems from end-to-endProfessional development programs, mentorship, and career advancementBenefits : Health, dental, vision insurance; 401(k); paid time off; and discretionary bonuses / equityHow to Apply :
Interested? Please submit your resume and a brief cover letter highlighting your hands-on ML experience and relevant projects or achievements.