Senior Machine Learning Engineer

Role : Senior Associate – Data Science & Machine Learning Experience : 5 to 8 Years

Work Mode : Hybrid (3 days office per week)

Location : Gurugram (GGN) / Bengaluru (BEN)

Notice Period : Immediate to 2 weeks ONLY

Employment Type : Full-Time

About the Role

We are seeking an experienced Data Science & Machine Learning Engineer who can design, build, and deploy advanced ML and AI-driven solutions. This role demands deep technical expertise in ML algorithms, deep learning architectures, LLMs, and model operationalization on cloud platforms.

Key Responsibilities

Build predictive models using classification, regression, clustering, and time-series techniques.

Perform feature engineering, algorithm selection, hyperparameter tuning, and model evaluation.

Build deep learning models using PyTorch or TensorFlow (CNNs, RNNs, transformers).

Develop GenAI applications using embeddings, LLMs, prompt engineering, RAG pipelines, LangChain, LlamaIndex, HuggingFace models.

Design and implement end-to-end ML pipelines from ingestion to deployment.

Build scalable data pipelines and work with cloud-based ML platforms (AWS / GCP / Azure ML).

Deploy, monitor, and maintain ML models using MLOps tools and CI / CD workflows.

Work closely with product and engineering teams to integrate ML solutions.

Must-Have Skills

Strong fundamentals : Statistics, Probability, Linear Algebra, Optimization

Machine Learning :

Classification, Regression, Clustering

Model evaluation (AUC, F1, Recall, ROC curves)

Cross-validation, bias-variance trade-off

Deep Learning :

CNNs, RNNs, Transformers

Hands-on PyTorch / TensorFlow

GenAI & NLP :

LLMs (GPT, LLaMA, Claude, etc.)

Embeddings, RAG, vector databases

Prompt engineering, model fine-tuning

Programming :

Python (NumPy, Pandas, Scikit-learn)

PyTorch / TensorFlow

SQL

MLOps : CI / CD

Model deployment & monitoring

Lifecycle management

Version control (Git) and cloud ML platforms (AWS / GCP / Azure)

Good to Have

Experience with Hugging Face models

Knowledge of Docker / Kubernetes

Exposure to reinforcement learning

Experience with A / B testing or experimentation frameworks

Required Candidate Information

(For screening – mandatory)

Total Experience

Relevant DS / ML Experience

Current CTC

Expected CTC

Notice Period ( Immediate – 2 weeks only )

Current Location

Preferred Location

LinkedIn Profile URL

How to Apply

Send your updated CV to :

vijay.s@xebia.com