Lead Analyst, AI Engineer(Data Science)

Required skills/Competencies

Programming Languages

Strong in Python, data structures, and algorithms.

Hands-on with NumPy, Pandas, Scikit-learn for ML prototyping.

Machine Learning Frameworks

Understanding of supervised/unsupervised learning, regularization, feature engineering, model selection, cross-validation, ensemble methods (XGBoost, LightGBM).

Deep Learning Techniques

Proficiency with PyTorch or TensorFlow/Keras

Knowledge of CNNs, RNNs, LSTMs, Transformers, Attention mechanisms.

Familiarity with optimization (Adam, SGD), dropout, batch norm.

LLMs & RAG

Hugging Face Transformers (tokenizers, embeddings, model fine-tuning).

Vector databases (Milvus, FAISS, Pinecone, ElasticSearch).

Prompt engineering, function/tool calling, JSON schema outputs.

Data & Tools

SQL fundamentals; exposure to data wrangling and pipelines.

Git/GitHub, Jupyter, basic Docker.

What are we looking for?

Solid academic foundation with strong applied ML/DL exposure.

Curiosity to learn cutting-edge AI and willingness to experiment.

Clear communicator who can explain ML/LLM trade-offs simply.

Strong problem-solving and ownership mindset.

- Min 5 yrs experience in the Mandatory Skills: Python, Deep Learning, Machine Learning, Algorithm Development and Image Processing

- 3.5 to 4 yrs proficiency with PyTorch or TensorFlow/Keras

Product or Semi conductor or Hardware Manufacturing company experience is a MUST.

Education/qualification: Preferrably from premier Institute like IIT, IISC, IIIT, NIT and BITS. Also regional tier 1 colleges.

Doctorate (Academic) Degree and 2 years related work experience; Master's Level Degree and related work experience of 5 years; Bachelor's Level Degree and related work experience of 7 years in building AI systems/solutions with Machine Learning, Deep Learning, and LLMs.