Software Engineer / Sr. Software Engineer (AI/ML)
- Compensation
- Not disclosed
- Location
- Mohali, PB, India
- Work setup
- Onsite
- Seniority
- Senior
- Employment
- Full time
- Experience
- 3+ years
- Category
- Ml / AI
- Posted
Skills
Must have
- ● 3–5 years of hands-on experience in Machine Learning, Data Science or AI/ML Engineering.
- ● Strong programming skills in Python.
- ● Strong understanding of supervised and unsupervised Machine Learning.
- ● Hands-on experience with scikit-learn, Pandas and NumPy.
- ● Practical experience with algorithms such as Linear/Logistic Regression, Random Forest, XGBoost/LightGBM, SVM and clustering techniques.
- ● Strong understanding of feature engineering, feature selection, model validation, cross-validation, hyperparameter tuning and model optimisation.
- ● Good understanding of ML evaluation metrics for classification, regression and ranking/prediction problems.
- ● Hands-on experience with PyTorch and/or TensorFlow.
- ● Good understanding of neural networks and Transformer architectures.
- ● Experience with at least one area such as NLP, Computer Vision, time-series/forecasting or recommendation systems.
- ● Strong working knowledge of SQL and experience working with large or messy real-world datasets.
- ● Experience exposing ML models through REST APIs/FastAPI or similar frameworks.
- ● Experience deploying and maintaining ML models in production.
- ● Working experience with Docker, Git and CI/CD.
- ● Experience with at least one cloud platform - AWS, Azure or GCP.
- ● Understanding of MLOps, model monitoring, versioning, logging and data/model drift.
Nice to have
- ● AI Agents and agentic workflows.
- ● Graph RAG or advanced retrieval techniques.
- ● Hugging Face Transformers.
- ● Fine-tuning / LoRA / QLoRA.
- ● MLflow, Kubeflow, Airflow, Prefect or similar.
- ● Snowflake, Databricks or modern data platforms.
- ● FAISS, pgvector, Pinecone, Qdrant or similar vector stores.
- ● Data engineering / ETL pipeline experience.
- ● Distributed processing using Spark.
- ● LLM/ML evaluation and observability.
- ● Experience working directly with clients and participating in technical discovery.
Full description
Job Title: Software Engineer/ Sr Software Engineer
Department: Product Engineering
Location: Mohali
Employment Type: Full Time
Experience Required: 3-5 years
Working Model: Work From Office
Role Summary
We are looking for a hands-on AI/ML Engineer with strong expertise in Machine Learning, applied Data Science and production ML systems.
The ideal candidate should be capable of working across the complete ML lifecycle - from data exploration, preprocessing and feature engineering to model development, evaluation, optimisation, deployment and monitoring.
While Machine Learning is the primary focus of this role, the candidate should also have practical exposure to modern AI technologies such as LLMs, RAG, embeddings and AI-powered applications, enabling them to contribute across a broad range of AI/ML projects.
Key Responsibilities
● Design, develop and optimise machine learning and predictive models for real-world business problems.
● Perform data exploration, preprocessing, feature engineering and feature selection across structured and unstructured datasets.
● Build solutions using regression, classification, clustering, ensemble methods, forecasting and deep learning.
● Develop ML solutions involving NLP, Computer Vision, recommendation systems or time-series data based on project requirements.
● Select appropriate algorithms and defi ne evaluation strategies and metrics for different ML problems.
● Perform hyperparameter tuning, model optimisation, validation and error analysis.
● Build scalable batch and real-time inference pipelines.
● Build and maintain MLOps pipelines covering training, deployment, model versioning, retraining, CI/CD and
monitoring.
● Monitor model accuracy, data/model drift, latency, cost and production reliability.
● Work with cloud platforms and modern ML infrastructure to deploy scalable solutions.
● Contribute to LLM/Generative AI applications, including RAG, embeddings, semantic search and AI integrations where required.
● Collaborate with clients, Product, Data Engineering and Software Engineering teams to translate business problems into practical AI/ML solutions.
● Evaluate new AI/ML technologies and rapidly build POCs to validate proposed approaches.