Job Title: AI/ML Engineer
Location: Hybrid (Pune)
Experience: 7–10 years
Tenure: 12 months rotation
Job Overview
We are looking for an experienced AI/ML Engineer to join our team and lead innovative solutions in Computer Vision, Natural Language Processing (NLP), and Predictive Analytics. The ideal candidate will have deep hands-on experience with Python, Open-Source ML frameworks, Big Data ecosystems, and statistical modelling (both predictive and inferential).
Key Responsibilities
Design, develop, and deploy machine learning models for NLP tasks (e.g., information extraction, classification, summarization, chatbot models).
Build and optimize Computer Vision pipelines for tasks such as object detection, image classification, OCR, and scene understanding.
Architect predictive and inferential statistical models using techniques like regression, Bayesian methods, and time-series forecasting.
Handle large-scale data using tools such as PySpark, Hadoop, or Dask and implement scalable ML pipelines.
Collaborate with data engineers and business stakeholders to define requirements, KPIs, and success metrics.
Conduct data modelling and feature engineering for structured and unstructured data.
Work with open-source frameworks like TensorFlow, PyTorch, Hugging Face, OpenCV, spaCy, and Scikit-learn.
Perform model evaluation, A/B testing, and explainability analysis using SHAP, LIME, etc.
Create REST APIs and integrate ML models into production systems using Flask, FastAPI, or containerized microservices.
Skills & Technologies
Programming & Libraries:
Python (advanced), NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow, OpenCV, spaCy, Hugging Face
ML/AI:
Supervised & unsupervised learning, deep learning (CNNs, RNNs, transformers), NLP, computer vision, recommender systems
Data & Big Data:
SQL, NoSQL, PySpark, Hive, Hadoop, Airflow, Kafka (nice to have)
Data Modeling:
ER modeling, dimensional modeling, time-series, inferential statistics, ANOVA, regression, causal inference
Tools & DevOps:
Git, Docker, MLflow, DVC, Jupyter, FastAPI, REST APIs, CI/CD for ML
Open Source & Platforms:
Experience with open-source communities or deploying models using open source MLOps stacks
Qualifications
Bachelor’s or Master’s in Computer Science, Data Science, AI/ML, Statistics, or related fields
5+ years of experience in machine learning or AI roles
Proven project experience in at least two domains: Computer Vision, NLP, Predictive Modeling
Hands-on experience with model deployment and MLOps best practices
Good to Have
Publications, patents, or open-source contributions
Experience with cloud platforms (AWS/GCP/Azure) for ML pipelines
Exposure to graph-based ML, reinforcement learning, or generative models
Pay: ₹100,000.00 - ₹120,000.00 per month
Work Location: Hybrid remote in Pune, Maharashtra (Pune, Pune District)
