Fullstack Job: Job Role: Sr. Machine Learning Engineer (Full Stac

Job Role: Sr. Machine Learning Engineer (Full Stack Developer)

Location: Remote

Visa: No, OPT, GC

EXP:1O YEARS

Key Responsibilities

Machine Learning & AI Development

• Design, develop, and optimize machine learning models for predictive analytics, recommendation systems, NLP, or computer vision.
• Implement, train, and fine-tune models using frameworks like TensorFlow, PyTorch, Scikit-learn, or Hugging Face.
• Perform data preprocessing, feature engineering, and model evaluation to ensure high-performance ML systems.
• Deploy and monitor ML models in production environments, ensuring scalability and reliability.

Full-Stack Development

• Develop and maintain backend services (APIs, microservices) using Python (FastAPI, Flask, Django).
• Build scalable, responsive front-end interfaces using React, Vue.js, or Angular.
• Integrate ML models into web and cloud-based applications with seamless user interactions.
• Ensure security, performance, and maintainability of the full-stack architecture.

DevOps & MLOps

• Automate deployment pipelines with CI/CD tools (Docker, Kubernetes, GitHub Actions, Jenkins).
• Implement MLOps best practices for model versioning, retraining, and monitoring.
• Solid understanding for how to optimize cloud infrastructure on AWS, Azure, or Google Cloud Platform for ML workloads.

Collaboration & Leadership

• Work closely with data scientists, product managers, and software engineers to align ML solutions with business objectives.
• Advocate for best practices in software engineering, ML model lifecycle management, and scalable architectures.
• Contribute to code reviews, technical documentation, and knowledge-sharing initiatives.

Key Qualifications

• 5+ years of hands-on experience in machine learning and full-stack development.
• Strong Python programming skills with experience in data structures, algorithms, and object-oriented programming.
• Proficiency in ML frameworks (TensorFlow, PyTorch, Scikit-learn) and data science libraries (Pandas, NumPy).
• Experience building RESTful APIs, GraphQL services, or gRPC-based microservices.
• Frontend experience with Angular, and state management (Redux, Vuex).
• Strong knowledge of SQL & NoSQL databases (PostgreSQL, MongoDB, Redis).
• Experience with Docker, Kubernetes, CI/CD pipelines, and cloud platforms (AWS/Google Cloud Platform/Azure).
• Solid understanding of data pipelines, ETL workflows, and distributed computing.
• Strong problem-solving skills and ability to optimize code for efficiency and scalability.
• Experience with LLMs (Large Language Models), Generative AI, and NLP.
• Familiarity with vector databases and embeddings (e.g., Pinecone, FAISS, Weaviate).
• Background in computer vision, reinforcement learning, or time-series forecasting.