Machine Learning Engineer

3 weeks ago

Pune, Maharashtra, India Impetus Full time
Job Summary:

We are looking for highly motivated and analytical Machine Learning Engineers with 1–3 years of experience in building scalable, production-ready AI/ML models. This role involves working on complex business problems using advanced ML/DL techniques across domains such as Natural Language Processing (NLP), Computer Vision, Time Series Forecasting, and Generative AI.

You will be responsible for end-to-end model development, deployment, and performance tracking while collaborating with cross-functional teams including data engineering, DevOps, and product.

Location: Noida / Gurugram / Indore / Bengaluru / Pune / Hyderabad

Experience: 1–3 Years

Education: BE / B.Tech / M.Tech / MCA / M.Com

Key Responsibilities:

Model Development & Experimentation

- Design and build machine learning models for NLP, computer vision, and time series prediction using supervised, unsupervised, and deep learning techniques.
- Conduct experiments to improve model performance via architectural modifications, hyperparameter tuning, and feature selection.
- Apply statistical analysis to validate and interpret model results.
- Evaluate models using appropriate metrics (e.g., accuracy, precision, recall, F1-score, AUC-ROC).

Data Handling & Feature Engineering

- Process large structured and unstructured datasets using Python, Pandas, and DataFrame APIs.
- Perform feature extraction, transformation, and selection tailored to specific ML problems.
- Implement data augmentation and enrichment techniques to enhance training quality.

Model Deployment & Productionization

- Deploy trained models to production environments using cloud platforms such as AWS (especially SageMaker).
- Containerize models using Docker and orchestrate deployments with Kubernetes.
- Implement monitoring, logging, and automated retraining pipelines for model health tracking.

Collaboration & Innovation

- Collaborate with data engineers and architects to ensure smooth data flow and infrastructure alignment.
- Explore and adopt cutting-edge AI/ML methodologies and GenAI frameworks (e.g., LangChain, GPT-3).
- Contribute to documentation, versioning, and knowledge-sharing across teams.
- Drive innovation and continuous improvement in AI/ML delivery and engineering practices.

Mandatory Technical Skills:

- Languages & Tools: Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch)
- Model Development: Deep Learning, NLP, Time Series, Computer Vision
- Cloud Platforms: AWS (especially SageMaker)
- Model Deployment: Docker, Kubernetes, REST APIs
- ML Ops: Model monitoring, performance logging, CI/CD
- Frameworks: LangChain (for GenAI), Transformers, Hugging Face

Preferred / Good to Have:

- Experience with Foundation Model tuning and prompt engineering
- Hands-on with Generative AI (GPT-3/4, OpenAI APIs, LangChain integrations)
- Certifications: AWS Certified Machine Learning – Specialty
- Experience with version control (Git), and experiment tracking tools (MLflow, Weights & Biases)

Soft Skills:

- Excellent communication and presentation abilities
- Strong analytical and problem-solving mindset
- Ability to work in collaborative, fast-paced environments
- Curiosity to learn emerging technologies and apply them to real-world problems

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