Sr AI/ML Solutions Architect - PostgreSQL (IN)

Expert proficiency in AI/ML model development, including classical ML, deep learning, NLP, and time series forecasting. 2. Excellent skills in Python, R, SQL, and Bash for data manipulation, model training, and automation. 3. Advanced expertise in TensorFlow, PyTorch, scikit-learn, pandas, NumPy, XGBoost, and LightGBM for building and deploying machine learning models. 4. Excellent knowledge of distributed computing and data engineering with Apache Spark, Spark Mllib, Apache Kafka, RabbitMQ, and DataBricks. 5. Solid understanding of relational databases, especially PostgreSQL and MySQL, for data storage and retrieval in ML workflows. 6. Expert ability to design secure, scalable architectures and implement best practices for AI/ML solution delivery.

Agentic AI, LangChain, LangGraph, Retrieval-Augmented Generation (RAG), Large Language Modeling, Vector Databases.

Skill Matrix – GenAI / ML (E3 Band)

The requirement is for a GenAI/ML professional with a total experience of 8+ years (Technical Experience) and 5+ years of relevant experience. The position is open across Pan India with preferred locations including Noida, Bangalore, Hyderabad, and Chennai. Candidates should be willing to attend office physically if required in these locations. The project type is primarily development-oriented. The role is suitable for both individual contributors and those with team handling experience.

No shift work is involved in this role, and there will be no customer interview process. The sell rate is not applicable for this requirement. The notice period is categorized as follows: Priority 1 includes candidates available within 0–30 days, Priority 2 includes those with 30–45 days, and Priority 3 includes candidates with 45–90 days.

The mandatory skills required include strong proficiency (Level 5) in Python and machine learning model development. Candidates must also have expertise in technologies such as Kafka, Spark, and PostgreSQL, along with hands-on experience in tools and frameworks like TensorFlow, PyTorch, Pandas, NumPy, and XGBoost.

In addition to the mandatory skills, the candidate should ideally have good-to-have proficiency (Level 4) in R, Bash scripting, scikit-learn, LightGBM, Spark MLlib, classical machine learning, deep learning, natural language processing, and time series forecasting. Exposure to Apache Spark, Apache Airflow, Apache Kafka, RabbitMQ, PostgreSQL, MySQL, and Databricks is also desirable.