We are looking for an experienced AI/ML Engineer with 4–9 years of hands-on experience in designing, developing, deploying, and maintaining machine learning and AI solutions.

The ideal candidate should have strong expertise in Python, Machine Learning, Deep Learning, NLP, Generative AI/LLMs, model development, and deployment. The candidate will work on building scalable AI solutions, developing ML models, integrating AI capabilities into applications, and taking models from experimentation to production.

Key Responsibilities

- Design, develop, train, evaluate, and deploy Machine Learning and AI models.
- Develop end-to-end ML pipelines from data preprocessing and feature engineering to model deployment and monitoring.
- Apply appropriate Machine Learning and Deep Learning algorithms to solve business problems.
- Work with structured and unstructured datasets to identify patterns and build predictive solutions.
- Perform data preprocessing, cleaning, feature engineering, model selection, and hyperparameter tuning.
- Develop and optimize models using frameworks such as Scikit-learn, TensorFlow, and PyTorch.
- Work on NLP, Generative AI, LLM, and/or Computer Vision use cases as required.
- Develop solutions using Large Language Models (LLMs) and integrate models through APIs or open-source frameworks.
- Build RAG (Retrieval-Augmented Generation) pipelines using embeddings and vector databases.
- Work with prompt engineering, model evaluation, fine-tuning, and LLM application development.
- Deploy ML/AI models as scalable APIs and integrate them with existing applications.
- Collaborate with software engineers, data engineers, product managers, and other stakeholders.
- Monitor model performance and improve models based on production feedback and changing data.
- Perform model optimization for accuracy, latency, scalability, and cost efficiency.
- Write clean, reusable, well-tested, and production-ready Python code.
- Participate in technical discussions, architecture decisions, code reviews, and documentation.

Required Technical SkillsProgramming

- Solid proficiency in Python.
- Strong understanding of Object-Oriented Programming, data structures, algorithms, and software engineering principles.




- Experience with libraries such as NumPy, Pandas, SciPy, etc.

Machine Learning

- Strong understanding of supervised and unsupervised learning.
- Hands-on experience with:
- Regression
- Classification
- Clustering
- Decision Trees / Random Forest
- Gradient Boosting / XGBoost / LightGBM
- Feature Engineering
- Model Evaluation
- Hyperparameter Optimization
- Strong understanding of ML metrics and model validation techniques.

Deep Learning

- Hands-on experience with TensorFlow and/or PyTorch.
- Understanding of:
- Neural Networks
- CNNs
- RNNs / LSTMs
- Transformers
- Transfer Learning
- Experience training, evaluating, and optimizing deep learning models.

Generative AI / LLM

- Hands-on experience with Generative AI and Large Language Models (LLMs) is preferred.
- Experience with models such as OpenAI, Azure OpenAI, Llama, Mistral, Gemini, or similar models.
- Knowledge of Prompt Engineering and LLM application development.
- Experience building RAG-based applications.
- Understanding of:
- Embeddings
- Vector Databases
- Semantic Search
- Chunking and Retrieval Strategies
- LLM Evaluation
- Experience with frameworks such as LangChain, LlamaIndex, or similar frameworks is a plus.
- Exposure to fine-tuning, LoRA/PEFT, or model optimization is an advantage.

NLP / Computer Vision

Experience in one or more of the following is preferred:

- Natural Language Processing (NLP)
- Text Classification
- Named Entity Recognition (NER)
- Sentiment Analysis
- Text Summarization
- Recommendation Systems
- Speech/Conversational AI
- Image Classification
- Object Detection
- OCR
- Computer Vision

MLOps & Deployment

- Experience deploying ML models into production environments.
- Knowledge of Docker and containerization.
- Experience developing ML APIs using FastAPI, Flask, or similar frameworks.
- Understanding of CI/CD and automated deployment pipelines.




- Experience with model versioning, experiment tracking, and monitoring.
- Exposure to tools such as MLflow, Kubeflow, Airflow, or similar technologies is preferred.
- Experience with cloud platforms such as AWS, Azure, or GCP.

Data & Database Skills

- Solid understanding of data preprocessing and data pipelines.
- Experience working with SQL databases.
- Knowledge of PostgreSQL/MySQL is preferred.
- Exposure to NoSQL databases such as MongoDB is a plus.
- Experience working with large datasets and distributed data processing is advantageous.
- Knowledge of Spark/PySpark is a plus.

Good to Have

- Experience with Azure OpenAI / AWS Bedrock / Google Vertex AI.
- Experience with vector databases such as FAISS, Pinecone, Weaviate, Milvus, or Chroma.
- Knowledge of microservices and distributed systems.
- Experience with Kubernetes.
- Knowledge of model serving frameworks.
- Experience optimizing LLM inference, latency, and cloud costs.
- Experience building AI-powered enterprise applications.
- Research experience, publications, or contributions to open-source AI/ML projects are a plus.

Required Experience

- 4–9 years of professional experience in AI/ML, Machine Learning Engineering, Data Science, or a closely related field.
- Strong hands-on experience with Python and Machine Learning.
- Experience taking ML/AI models from development/experimentation to production.
- Strong understanding of ML concepts, algorithms, model evaluation, and deployment.
- Experience working on real-world AI/ML projects in a production environment.

Educational Qualification

- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related field.
- Equivalent practical experience may also be considered.

Preferred Tech Stack

Python | Machine Learning | Scikit-learn | TensorFlow / PyTorch | NLP | Generative AI | LLMs | RAG | LangChain / LlamaIndex | OpenAI / Azure OpenAI | Vector Databases | FastAPI / Flask | Pandas | NumPy | SQL | Docker | MLflow | AWS / Azure / GCP | Git | CI/CD

Pay: ₹60,000.00 - ₹100,000.00 per month

Benefits:

- Provident Fund

Work Location: In person

📌 AI/ML Engineer (Exp:4-9yrs) (India)
🏢 ZecData Technology
📍 India