Peak Hire Solutions

JOB DESCRIPTION/PREFERRED QUALIFICATIONS: 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. MINIMUM QUALIFICATIONS: 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. MUST-HAVES: Education/qualification: Preferably from premier Institute like IIT, IISC, IIIT, NIT and BITS. Also regional tier 1 colleges. Doctorate (Academic) Degree and 2 years related work experience; or Master's Level Degree and related work experience of 5 years; or Bachelor's Level Degree and related work experience of 7 years 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 Candidates from engineering product companies have higher chances of getting shortlisted (current company or past experience)