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 creative 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)

📌 AI/ML Engineer (India)
🏢 Potla Tech Solutions
📍 India