About The Role
We are looking for a Senior Machine Learning Engineer to help transform innovative AI solutions into scalable, production-grade products. In this role, you will work at the intersection of Machine Learning, Software Engineering, and Cloud Technologies, partnering with AI, Computer Vision, NLP, Data Engineering, and MLOps specialists to deliver reliable, secure, and observable ML systems on AWS.
You will play a key role in bringing AI-powered capabilities to production, building robust data and model pipelines, and establishing engineering best practices that enable long-term scalability and business impact.
Responsibilities
- Design, develop, and maintain scalable machine learning services, data pipelines, and cloud-native applications on AWS
- Productionize AI, Computer Vision, NLP, and predictive modeling solutions, ensuring reliability, performance, and operational excellence
- Build high-quality, maintainable, and well-tested software following modern engineering standards and best practices
- Collaborate with cross-functional teams to develop end-to-end ML solutions, from data preparation and feature engineering to model deployment and monitoring
- Implement automated model evaluation, performance monitoring, and continuous validation processes to support production systems
- Contribute to cloud infrastructure, deployment automation, and CI/CD processes to ensure efficient software delivery
- Create and maintain technical documentation, including architecture designs, operational procedures, and engineering guidelines
- Participate in code reviews, architectural discussions, and continuous improvement initiatives to strengthen engineering excellence across the team
Requirements
- Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, or a related field
- Strong commercial experience in Machine Learning Engineering and software development, including delivering production-ready ML solutions
- Hands-on experience building and operating cloud-based applications and machine learning systems on AWS
- Strong proficiency in Python and solid knowledge of software development best practices, including testing, code reviews, observability, and CI/CD
- Experience working with modern machine learning and deep learning frameworks, preferably PyTorch
- Practical experience developing containerized applications with Docker and deploying solutions in Kubernetes environments
- Understanding of distributed systems, cloud-native architectures, and scalable data processing solutions
- Experience working in Agile development environments and collaborating with cross-functional engineering teams
- Strong communication skills and ability to document technical designs, decisions, and operational processes
NICE TO HAVE
- Experience deploying and supporting Computer Vision, Natural Language Processing, or forecasting solutions in production
- Familiarity with model serving frameworks such as vLLM, Triton Inference Server, or TorchServe
- Experience optimizing ML inference workloads using techniques such as quantization, ONNX, or TensorRT
- Experience with ML lifecycle and experiment management tools, including MLflow or Weights & Biases
- Experience building solutions in regulated industries such as Healthcare, Life Sciences, Financial Services, or Insurance
- Experience using AI-powered developer tools, such as GitHub Copilot or Claude Code, to improve engineering productivity
SoftServe is an equal opportunity employer. Qualified applicants will receive consideration regardless of race, color, ancestry, ethnicity, national origin, religion, sex, sexual orientation, gender identity or expression, age, citizenship, disability, health condition, marital or family status, veteran status, or any other characteristic protected by applicable law.