Job Profile :

Machine Learning & Deep Learning
Design, train, fine?tune, and evaluate machine learning and deep learning models for real?world enterprise use cases.
Develop supervised, unsupervised, and self?supervised learning approaches.
Implement and optimize neural network architectures (CNNs, RNNs, Transformers).
Perform feature engineering, data preprocessing, and model optimization.
Define and tune loss functions, evaluation metrics, and validation strategies.
LLM & Advanced AI Models
Train, fine?tune, and evaluate large language models (instruction tuning, adapters, LoRA).
Build domain?specific language models and embedding models.
Implement prompt?based and model?based approaches depending on use case requirements.
Ensure model robustness, reliability, and explainability.
Data & Experimentation
Work with structured and unstructured data (SQL, JSON, text, logs).
Design experiments, perform error analysis, and iterate models based on results.
Document model assumptions, limitations, and performance characteristics.
MLOps & Deployment
Package and deploy models into production environments.
Collaborate with platform and DevOps teams on CI/CD pipelines for ML models.
Monitor model performance, drift, and data quality over time.

Delivery & Support model:





•Support model: Standard Business Hours 5x9 (Mo - Fr , 08:00 – 17:00 (CET/CEST, DST included).

What should you bring along :

Expected skill Sets and experience that the candidates should bring along.

Key Qualifications and Skills:
Strong background in machine learning and deep learning theory and practice.
Proven experience training own models end?to?end (not only consuming APIs).
Solid Python skills for data science and ML development.
Experience working in enterprise or industrial environments.
Structured, analytical mindset with solid problem?solving skills.

Must have technical skill :
Python (advanced)
Machine Learning & Deep Learning
PyTorch and/or TensorFlow
Model training, fine?tuning, and evaluation
Feature engineering & data preprocessing
LLMs and embeddings
Experiment tracking and model evaluation

Positive to have technical skills :
Experience with Transformers and contemporary LLM architectures
MLOps tools (MLflow, model registries, monitoring)
Distributed training or GPU acceleration
Automotive or enterprise data domains
Experience with open?source models (LLaMA, Mistral, Qwen)

📌 Data Scientist Pune
🏢 BMW TechWorks
📍 Pune