As a Senior ML Engineer at Provectus, you'll be responsible for designing, developing, and deploying production\-grade machine learning solutions for our clients. You will work on complex ML problems, mentor junior engineers, and contribute to building ML accelerators and best practices. ### **Core Responsibilities:** * 1\. Technical Delivery (60%) * Design and implement end\-to\-end ML solutions from experimentation to production * Build scalable ML pipelines and infrastructure * Optimize model performance, efficiency, and reliability * Write clean, maintainable, production\-quality code * Conduct rigorous experimentation and model evaluation * Troubleshoot and resolve complex technical challenges * 2\. Collaboration and Contribution (25%) * Mentor junior and mid\-level ML engineers * Conduct code reviews and provide constructive feedback * Share knowledge through documentation, presentations, and workshops * Collaborate with cross\-functional teams (DevOps, Data Engineering, SAs) * Contribute to internal ML practice development * 3\. Innovation and Growth (15%) * Stay current with ML research and emerging technologies * Propose improvements to existing solutions and processes * Contribute to the development of reusable ML accelerators * Participate in technical discussions and architectural decisions ### **Requirements:** * Comfortable with standard ML algorithms and underlying math. * Strong hands\-on experience with LLMs in production, RAG architecture, and agentic systems * AWS Bedrock experience strongly preferred * Practical experience with solving classification and regression tasks in general, feature engineering. * Practical experience with ML models in production. * Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines. * Solid software engineering skills (i.e., ability to produce well\-structured modules, not only notebook scripts). * Python expertise, Docker. * English level \- strong Intermediate. * Excellent communication and problem\-solving skills. ### **Will be a plus:** * Practical experience with cloud platforms (AWS stack is preferred, e.g. Amazon SageMaker, ECR, EMR, S3, AWS Lambda). * Practical experience with deep learning models. * Experience with taxonomies or ontologies. * Practical experience with machine learning pipelines to orchestrate complicated workflows. * Practical experience with Spark/Dask, Great Expectations. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.