13 days ago
Remote, IndiaSenior
Responsibilities
- Design, develop, and deploy scalable machine learning models and AI applications that solve complex business problems.
- Design and develop search and chat applications using agentic AI.
- Build AI paved paths for the engineering organization.
- Design experiments to evaluate model and application performance, then analyze results to improve performance.
- Evaluate, fine-tune, and deploy LLMs and foundation models using RAG, guardrails, and prompt engineering practices.
- Write production-quality Python code for feature engineering, model evaluation, and interface services and APIs.
- Build high-performance data ingestion pipelines and work across AWS, data engineering, ML/GenAI, and data ingestion technologies.
- Develop Spring AI solutions, including MCPs, tools, and plugins.
- Work with CI/CD pipelines using GitHub Actions, GitLab, and Jenkins.
- Mentor engineers on ML best practices without direct people management.
- Collaborate with engineering, product, domain, and business stakeholders and explain technical concepts to nontechnical audiences.
Requirements
- 8–10 years of overall experience in data engineering, ingestion, AI/ML, or GenAI-related projects.
- At least 5 years of experience on AI, GenAI, or ML projects.
- Master’s degree, preferably in Computer Science, Data Science, Mathematics, Actuarial Science, Engineering, or a related field.
- Experience with Python or Spark, including Scala Spark or PySpark, and machine learning libraries such as TensorFlow, Keras, and PyTorch.
- Familiarity with Java, Spring AI, and Spring Boot services.
- Experience with data cleaning, feature engineering, data transformation, and other data engineering tasks.
- Knowledge of deep learning architectures and techniques, including convolutional neural networks, recurrent neural networks, and reinforcement learning.
- Familiarity with AWS data and data science tools including SageMaker, Glue, and Lambda.
- Experience with Agile and DevOps development processes.
- Strong ability to communicate complex technical concepts clearly to nontechnical audiences.
Benefits
- Health benefits starting on Day One, wellbeing programs, retirement plans, continuing education and training, and career growth opportunities.
- Global organization with a collaborative, high-performing team and inclusive culture.
- Virtual interviews are conducted by video, with a camera-on culture; occasional travel to a physical office may be required.
- Employment is contingent on successfully completing a background check, which may include identity, education, employment, criminal, sanctions-list, credit, or drug-test checks.
Tech Stack
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