Mid ML Engineer - India

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, Data Science, or a related technical field.
• 3–5 years of professional experience in machine learning engineering, applied ML, or a closely related role.
• Strong proficiency in Python and hands-on experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Experience building and deploying ML pipelines in production environments.
• Working knowledge of MLOps tools and practices including MLflow, Kubeflow, Airflow, or similar orchestration frameworks.
• Experience with cloud platforms (AWS SageMaker, Azure ML, or GCP Vertex AI) for training, deployment, and serving.
• Proficiency in SQL and experience working with large-scale datasets.
• Experience with Docker, Kubernetes, and CI/CD pipelines for ML workflows.
• Solid understanding of model evaluation, hyperparameter tuning, and feature engineering techniques.
• Familiarity with REST APIs and microservices architecture for model serving.

Preferred Qualifications

• Experience with deep learning architectures such as Transformers, CNNs, or RNNs.
• Familiarity with feature stores (Feast, Tecton) and data versioning tools (DVC, LakeFS).
• Experience with model monitoring and observability tools (Evidently AI, WhyLabs, or Prometheus/Grafana).
• Exposure to distributed training frameworks and GPU-accelerated computing.
• Experience with A/B testing and experimentation frameworks for ML models.
• Knowledge of data engineering tools such as Spark, Kafka, or dbt.

Why Join Cogniify?

Perks And Benefits Of Working With Us

• Internet allowance
• Laptop
• PF
• Paid PTO
• Annual Bonus
• Graduity
• Yearly Team building experiences
• Mentorship and sponsorship opportunities
• Manager resources and support
• Life & accidental insurance for additional protection.
• We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other protected characteristic.