Job Description:
Designing and implementing machine learning models and systems, and optimizing algorithms for real-world applications. Join S.T.A.R.S Pvt Ltd to build scalable ML infrastructure and deploy intelligent systems that solve complex business challenges. You will work on end-to-end machine learning pipelines, from data preprocessing to model deployment and monitoring.
Collaborate with data scientists and software engineers to transform research prototypes into production-ready solutions. This role focuses on engineering excellence, system scalability, and delivering robust ML applications that serve millions of users across diverse industries including fintech, healthcare, and e-commerce.
Responsibilities:
- Design and implement scalable machine learning pipelines and deployment infrastructure
- Optimize ML models for performance, latency, and resource efficiency in production environments
- Build automated training, testing, and monitoring systems for continuous model improvement
- Collaborate with data science teams to productionize research models and experimental algorithms
- Develop APIs and microservices for ML model serving and real-time inference capabilities
- Implement MLOps best practices including version control, CI/CD, and automated deployment workflows
Preferred Qualifications:
- Bachelor's or Master's degree in Computer Science, Engineering, or related technical field
- 2+ years experience in machine learning engineering or software development with ML focus
- Proficiency in Python, Docker, Kubernetes, and cloud platforms (AWS, GCP, Azure)
- Experience with ML frameworks (TensorFlow, PyTorch) and production deployment tools
- Strong understanding of software engineering principles, data structures, and algorithms
- Knowledge of distributed systems, databases, and API development for ML applications
