Location: [Hyderabad]
Job Type: Full-time
Experience Level: Mid-Level (2+ Years)
About the Role:
We are looking for a motivated AI/ML Engineer with 2+ years of hands-on experience in developing, deploying, and maintaining machine learning models. The ideal candidate is passionate about building intelligent systems and solving real-world problems using data-driven techniques.
Key Responsibilities:
- Design, build, and deploy machine learning models to solve complex business problems.
- Collect, clean, and preprocess large datasets for modeling.
- Conduct exploratory data analysis (EDA) to extract actionable insights.
- Implement and fine-tune models using frameworks like TensorFlow, PyTorch, or scikit-learn.
- Develop production-ready ML pipelines using tools like MLflow, Airflow, or Kubeflow.
- Collaborate with data engineers, product managers, and other stakeholders to define project requirements and goals.
- Monitor and evaluate model performance and retrain models as needed.
- Document experiments, model parameters, and results for reproducibility.
Requirements:
- 2+ years of hands-on experience in machine learning and AI projects.
- Proficiency in Python and ML libraries such as scikit-learn, TensorFlow, or PyTorch.
- Solid understanding of machine learning algorithms: supervised, unsupervised, and basic deep learning techniques.
- Experience working with data manipulation tools like Pandas, NumPy, and SQL.
- Familiarity with model evaluation metrics and validation techniques.
- Experience with version control tools (e.g., Git) and collaborative workflows.
- Basic understanding of software engineering principles and model deployment.
- Strong problem-solving and communication skills.
Nice to Have:
- Experience with cloud platforms (AWS/GCP/Azure) for ML services.
- Exposure to MLOps tools (e.g., MLflow, Airflow, Docker, Kubernetes).
- Familiarity with NLP, computer vision, or time series analysis.
- Contributions to open-source ML projects or publications.
- Understanding of data privacy, model explainability, or ethical AI practices.
Benefits:
- Competitive salary and performance bonuses
- Flexible work environment (remote/hybrid)
- Learning and development budget
- Access to cutting-edge tools and resources
- Mentorship and career growth opportunities
