Note: The job is a remote job and is open to candidates in USA. Innovatech Staffing is seeking a Machine Learning Engineer to transform theoretical ML models into robust, scalable software products. The role involves developing machine learning applications, managing databases, and ensuring cloud security compliance.

Responsibilities

• Productizing ML Models : Bridge the gap between prototype and production by transforming theoretical ML models into robust, scalable, and highly performant user-facing software products
• Model & Application Development: Design, build, and optimize machine learning application layers, applying rigorous mathematical and statistical methodologies to ensure model accuracy and validity
• Back-End Engineering : Partner with the CTO and AI Director to develop robust Python-based back-end systems and server frameworks to support core AI features
• Architecture Definition : Take ownership of defining model architectures and integrating them seamlessly into our core product ecosystem
• Database & Security Management : Securely manage relational databases (PostgreSQL), ensuring strict application-level data security and compliance for sensitive health data
• MLOps & Infrastructure Support : Support the deployment and orchestration of models using Google Kubernetes Engine (GKE) on Google Cloud Platform (GCP), ensuring basic automated pipeline tracking and environment stability
• Cloud Security Compliance: Implement cloud security best practices, including access authorization and airgapping strategies to protect operational data environments

Skills

• Proven track record with 5+ years of software development experience heavily focused on Python programming and server frameworks
• Strong quantitative background with deep knowledge of linear algebra, calculus, probability, statistics, and optimization techniques underlying modern ML algorithms
• Demonstrable experience taking models out of research environments (notebooks) and successfully engineering them into commercialized products with high reliability
• Strong, demonstrable experience defining model architectures and developing production-grade ML applications
• 5+ years of experience working within Google Cloud Platform (GCP), with foundational knowledge of Google Kubernetes Engine (GKE) for model serving
• 5+ years of experience with PostgreSQL, including database security implementations
• Strong analytical skills and problem-solving abilities, with a proven track record of meeting tight deadlines in a fast-paced environment
• Experience with MLOps frameworks, continuous deployment for machine learning models, or model monitoring pipelines
• Foundational knowledge of or experience with Elixir/Phoenix is highly ideal

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