Nexify Infosystems

Senior Data Science and Machine Learning Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Data Science and Machine Learning Engineer, lasting 12+ months, with a pay rate of "unknown." Candidates must have 12+ years of experience, a Bachelor's degree, and strong skills in Python, ML model development, and cloud platforms.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
Unknown
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πŸ—“οΈ - Date
February 27, 2026
πŸ•’ - Duration
More than 6 months
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🏝️ - Location
Remote
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πŸ“„ - Contract
Unknown
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πŸ”’ - Security
Unknown
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πŸ“ - Location detailed
United States
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🧠 - Skills detailed
#Data Science #Observability #Python #Code Reviews #AWS (Amazon Web Services) #Security #Monitoring #AI (Artificial Intelligence) #Compliance #Database Systems #Libraries #Mathematics #Computer Science #Azure #Pandas #NoSQL #Deployment #Version Control #Leadership #Kubernetes #MySQL #TensorFlow #ML Ops (Machine Learning Operations) #ML (Machine Learning) #NumPy #PostgreSQL #Data Governance #Data Engineering #PySpark #SQL (Structured Query Language) #Docker #A/B Testing #GIT #Statistics #GCP (Google Cloud Platform) #Spark (Apache Spark) #PyTorch #Strategy #Cloud #Deep Learning #Data Strategy #Data Pipeline
Role description
Job Title: Senior Data Science and Machine Learning Engineer Location: Remote Duration: 12+ Months Must have 12+ years of experience. Job Summary β€’ 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. β€’ 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 β€’ Develop, deploy, and maintain machine learning models in production environments. β€’ Collaborate with data scientists, analysts, and product managers to define and deliver data-driven features. β€’ Ensure high-quality data through monitoring, validation, and robust testing frameworks. β€’ Architect and maintain data platforms and tools for experimentation, model serving, and feature engineering. β€’ Explore and integrate Large Language Models (LLMs) and other generative AI approaches into business applications and data workflows. β€’ Contribute to code reviews, technical design discussions, and best practices for the team. β€’ Mentor and guide junior engineers/data scientists, fostering technical excellence and career growth. β€’ 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 β€’ 5+ years of experience in data engineering, machine learning engineering, or related roles. β€’ Strong proficiency in Python (Pandas, NumPy, PySpark, or similar). β€’ Solid understanding of ML model development, training, and deployment pipelines. β€’ Experience with ML model monitoring and observability frameworks. β€’ Experience with deep learning frameworks(TensorFlow, PyTorch). β€’ Familiarity with CI/CD, version control (Git),and modern ML Ops practices. Nice-to-Have β€’ Contributions to open-source Data Science / Machine Learning libraries or frameworks. β€’ Hands-on experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). β€’ Proficiency with SQL and database systems (PostgreSQL, MySQL, or NoSQL alternatives). β€’ Exposure to data governance, security, and compliance requirements. β€’ Knowledge of experiment design (A/B testing, causal inference). Soft Skills β€’ Strong problem-solving and analytical skills. β€’ Excellent communication and collaboration abilities across technical and non-technical teams. Leadership qualities and the ability to drive projects independently.