Senior Data Science and Machine Learning Engineer || Only W2

Senior Data Science and Machine Learning Engineer

Fully Remote but candidate must be in EST or CST

Duration : 12+ Months

 Job Summary

·         We are seeking a Senior Data Science Engineer to design, build, and scale data-driven systems that power advanced analytics and machine learning across our organization. This role sits at the intersection of software engineering and data science; you’ll be responsible for building robust data pipelines, enabling experimentation, and deploying production-ready machine learning models.

·         As a senior team member, you will mentor junior engineers and data scientists, influence architectural decisions, and help shape the long-term AI and data strategy.‍

Key Responsibilities

• Develop, deploy, and maintain machine learning models in production environments.
• Collaborate with data scientists, analysts, and product managers to define and deliver data-driven features.
• Ensure high-quality data through monitoring, validation, and robust testing frameworks.
• Architect and maintain data platforms and tools for experimentation, model serving, and feature engineering.
• Explore and integrate Large Language Models (LLMs) and other generative AI approaches into business applications and data workflows.
• Contribute to code reviews, technical design discussions, and best practices for the team.
• Mentor and guide junior engineers/data scientists, fostering technical excellence and career growth.
• Stay current with emerging technologies in Data Science, Machine Learning, LLM Ops, ML Ops.‍

 Education Requirement

Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.
Master’s degree or PhD is a strong plus.

 Experience

·         5+ years of experience in data engineering, machine learning engineering, or related roles.

·         Strong proficiency in Python (Pandas, NumPy, PySpark, or similar).

·         Solid understanding of ML model development, training, and deployment pipelines.

·         Experience with ML model monitoring and observability frameworks.

·         Experience with deep learning frameworks(TensorFlow, PyTorch).

·         Familiarity with CI/CD, version control (Git),and modern ML Ops practices.

 Nice-to-Have

·         Contributions to open-source Data Science / Machine Learning libraries or frameworks.

·         Hands-on experience with cloud platforms (AWS, Google Cloud Platform, or Azure) and containerization (Docker, Kubernetes).

·         Proficiency with SQL and database systems (PostgreSQL, MySQL, or NoSQL alternatives).

·         Exposure to data governance, security, and compliance requirements.

·         Knowledge of experiment design (A/B testing, causal inference).

 Soft Skills

·         Strong problem-solving and analytical skills.

·         Excellent communication and collaboration abilities across technical and non-technical teams.

Leadership qualities and the ability to drive projects independently.