AI Engineer
Role Overview
Contribute to data-driven and AI-powered solutions for enterprise customers and internal platforms.
Work across data engineering, machine learning, generative AI, and cloud-native analytics using AWS technologies.
The role is presented as suitable for professionals building a career in Data Engineering, Machine Learning, Applied AI, MLOps, and Generative AI.
Key Skills for This Role
Full Job Posting
Role overview
Contribute to data-driven and AI-powered solutions for enterprise customers and internal platforms.
Work across data engineering, machine learning, generative AI, and cloud-native analytics using AWS technologies.
The role is presented as suitable for professionals building a career in Data Engineering, Machine Learning, Applied AI, MLOps, and Generative AI.
Responsibilities
- Build and maintain data pipelines; prepare, cleanse, transform, and engineer features from structured and unstructured data.
- Support scalable processing and analytics workflows and maintain data quality, reliability, and consistency.
- Support machine learning model development, training, testing, deployment, evaluation, experimentation, and optimization.
- Contribute to predictive analytics, classification, forecasting, recommendation, and NLP use cases.
- Experiment with LLMs and GenAI frameworks; help build AI assistants, RAG applications, and GenAI workflows.
- Design and optimize prompts, evaluate model outputs, and improve response quality.
- Assist with AWS data and AI workload deployment and management.
- Collaborate across CloudOps, DevOps, Product, Architecture, and customer teams; document work and contribute reusable assets.
Required qualifications
- Bachelor's or master's degree in computer science, data science, AI, machine learning, statistics, mathematics, or a related technical discipline.
- 0–2 years of relevant experience in data science, machine learning, data engineering, applied AI, or a related field.
- Strong Python programming skills and experience with SQL and relational databases.
- Understanding of data structures, algorithms, statistics, machine learning fundamentals, software engineering principles, and cloud computing.
- Familiarity with Pandas, NumPy, Scikit-Learn, and TensorFlow or PyTorch.
- Familiarity with GenAI frameworks or APIs such as LangChain, LangGraph, Hugging Face, OpenAI, or Anthropic.
- Understanding of prompt engineering, RAG, and AI application development.
- Strong analytical, problem-solving, communication, and collaboration abilities.
Desired qualifications
- Exposure to AWS services such as SageMaker, Bedrock, Glue, Athena, or Redshift.
- Familiarity with Spark, Kafka, Snowflake, or similar data platforms.
- Exposure to MLOps tools such as MLflow, Kubeflow, or SageMaker Pipelines.
- Hackathons, Kaggle competitions, research projects, open-source contributions, and relevant AWS certifications are desirable.
Compensation
- Pay is up to ₹700,000 per year.
Workplace
- Work location is in person at the employer's Pune offices.
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