Job Description
About the Role :
We are seeking a skilled Data / ML Engineer to design, develop, and deploy scalable machine learning pipelines and data engineering solutions that power AI-driven applications. The ideal candidate should have strong expertise in data processing, machine learning frameworks, and MLOps, with hands-on experience building production-grade ML systems and integrating them into enterprise applications.
Key Responsibilities :
- Design, develop, and maintain scalable data pipelines for machine learning and analytics workloads.
- Build and deploy end-to-end machine learning pipelines for data ingestion, feature engineering, model training, validation, deployment, and monitoring.
- Develop and optimize ML models using frameworks such as PyTorch or TensorFlow.
- Process and transform large-scale datasets using Apache Spark, Databricks, or similar distributed data processing platforms.
- Design efficient data models and write optimized SQL queries for analytics and model training.
- Implement feature engineering, data validation, and data quality processes.
- Develop and maintain ML experimentation frameworks to support rapid model development and evaluation.
- Implement MLOps best practices, including model versioning, CI/CD pipelines, automated deployments, monitoring, and retraining workflows.
- Integrate machine learning pipelines with enterprise applications, APIs, and cloud-native platforms.
- Collaborate with data scientists, software engineers, and business stakeholders to translate business requirements into scalable AI solutions.
- Monitor production ML systems, troubleshoot issues, and optimize performance, scalability, and reliability.
- Maintain technical documentation and follow engineering best practices throughout the ML lifecycle.
Required Skills & Qualifications :
- Bachelor's degree in Computer Science, Information Technology, Data Science, Engineering, or a related field.
- Strong proficiency in Python for data engineering and machine learning.
- Hands-on experience with PyTorch, TensorFlow, or equivalent ML frameworks.
- Strong experience with Apache Spark, Databricks, or distributed data processing technologies.
- Expertise in SQL, data modeling, and relational databases.
- Solid understanding of machine learning lifecycle management and MLOps concepts.
- Experience building scalable data pipelines and production-grade ML workflows.
- Familiarity with cloud platforms such as AWS, Azure, or GCP.
- Experience with Git, CI/CD pipelines, Docker, and containerized deployments.
- Strong analytical, problem-solving, and communication skills.
Preferred Skills :
- Experience with ML orchestration tools such as MLflow, Kubeflow, Airflow, or Vertex AI.
- Knowledge of vector databases, Generative AI, or LLM-based applications.
- Experience with Kubernetes and cloud-native deployment architectures.
- Exposure to streaming platforms such as Kafka or Spark Streaming.
No Referrers Available
There are currently no referrers available for this job. You can still apply, will let you know once there is any referrer available.