This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Machine Learning Engineer / Data Scientist based in the United States.
This role sits at the core of building and deploying end-to-end machine learning solutions that directly influence business outcomes. You will work across the full ML lifecycle, from framing ambiguous business problems to delivering production-ready models and monitoring their real-world performance. The position combines hands-on data science, applied machine learning, and strong stakeholder collaboration in a client-facing environment. You will work with complex, real-world datasets to design features, train models, and translate insights into actionable decisions. A key part of the role involves ensuring models are not only accurate but also scalable, explainable, and production-ready. It is a high-impact position where technical depth, communication, and business understanding all play a critical role.
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Accountabilities:
- Translate business challenges into machine learning problems such as classification, regression, forecasting, clustering, and anomaly detection.
- Collaborate with stakeholders to define success metrics, constraints, and evaluation strategies aligned with business goals.
- Extract, clean, and analyze data using Python and SQL, ensuring data quality, consistency, and readiness for modeling.
- Design and build robust feature engineering pipelines, including transformations, encoding, scaling, and aggregation logic.
- Develop, tune, and validate machine learning models across supervised, unsupervised, and time series use cases.
- Apply deep learning techniques using frameworks such as PyTorch or TensorFlow/Keras when appropriate.
- Perform model evaluation, error analysis, and interpretability analysis using metrics, SHAP, and cohort-based insights.
- Support deployment efforts by collaborating on APIs or batch pipelines and contributing to MLOps practices such as monitoring and retraining.
- Communicate findings, trade-offs, and recommendations clearly to both technical and non-technical stakeholders.
- Document methodologies, assumptions, and results to ensure reproducibility and transparency.
Requirements:
- 3–8 years of experience in data science, machine learning engineering, or applied ML roles.
- Strong proficiency in Python for data analysis and modeling (pandas, NumPy, scikit-learn or equivalent).
- Advanced SQL skills including joins, window functions, and performance-aware querying.
- Solid foundation in statistics, experimentation, and probabilistic reasoning.
- Hands-on experience with classification, regression, time series forecasting, and clustering techniques.
- Experience with deep learning frameworks such as PyTorch or TensorFlow/Keras.
- Ability to work with messy, ambiguous datasets and translate them into structured ML solutions.
- Strong communication skills with the ability to explain complex results in simple, actionable terms.
- Preferred: experience with Databricks, cloud platforms (AWS/GCP/Azure), orchestration tools (Airflow, Prefect, Dagster), and MLOps workflows.
- Preferred: exposure to production deployment, model monitoring, and retraining pipelines.
- Must be able to work in the United States without immigration sponsorship.
Benefits:
- Opportunity to work on end-to-end machine learning solutions with measurable business impact.
- Remote-friendly work environment with collaboration across distributed teams.
- Exposure to diverse industries and real-world enterprise AI use cases.
- Strong technical growth through hands-on work with modern ML, cloud, and MLOps tools.
- Collaborative, learning-oriented environment with cross-functional stakeholders.
- Opportunity to contribute to production-grade AI systems and scalable ML infrastructure.
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How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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