Job Title: AI/ML Engineer
Location: Remote
Experience: 2–6 Years
Department: AI Solutions
Employment Type: Full-time
Salary: 15 to 25 LPA
About the Role
We are looking for a highly skilled AI/ML Engineer to design, build, and deploy intelligent systems that solve real business problems. The ideal candidate will have hands‑on experience in machine learning, deep learning, data pipelines, and production‑grade model deployment.
You will collaborate with cross‑functional teams, data engineers, and product leads to build AI‑driven applications aligned with organizational goals.
Key Responsibilities
- Design, train, test, and optimize ML and deep learning models
- Build scalable machine learning pipelines using modern frameworks
- Work with large datasets, perform preprocessing, feature engineering, and data validation
- Implement algorithms for classification, regression, NLP, computer vision, or recommendation systems
- Deploy ML models into production using cloud platforms (Azure, AWS, or GCP)
- Integrate models into applications through APIs, microservices, or containerized environments
- Monitor model performance and continuously refine algorithms
- Collaborate with data teams to improve data quality and architecture
- Experiment with new techniques, evaluate research papers, and implement PoCs
- Optimize system performance, reduce latency, and ensure high accuracy
- Document processes, workflows, and model behavior for future reference
Required Skills
- Strong proficiency in Python and ML libraries:
- TensorFlow, PyTorch, Scikit-learn
- Pandas, NumPy
- Experience with ML model development, training, and hyperparameter tuning
- Solid understanding of:
- Supervised & unsupervised learning
- Deep learning architectures (CNNs, RNNs, Transformers)
- NLP techniques
- Time-series forecasting
- Experience with cloud platforms: Azure / AWS / GCP
- Knowledge of REST APIs, microservices, and containerization (Docker/Kubernetes)
- Strong problem‑solving and analytical skills
Good to Have
- Experience with LLMs, GenAI, prompt engineering, vector databases
- Experience with MLOps tools (MLflow, DVC, Kubeflow, SageMaker, Vertex AI)
- Familiarity with Data Engineering concepts (ETL, pipelines, big data tools)
- Understanding of model governance, security, and responsible AI
- Knowledge of CI/CD for ML workflows
Education
- Bachelor's or Master's degree in Computer Science, AI/ML, Data Science, Engineering, or related fields
Why Join Us
- Work on cutting-edge AI & Generative AI projects
- Opportunity to build scalable solutions for enterprise clients
- Collaborative team environment with continuous learning
- Freedom to experiment and create impactful AI systems
- Career growth in a fast‑evolving AI landscape
