Machine Learning Engineer (4-9 yrs)

We are seeking a highly skilled and motivated Machine Learning Engineer with MLOps experience to join our team.

The ideal candidate will have a strong background in machine learning, data science, and software engineering, with a particular focus on deploying and maintaining machine learning models in production environments.

You will work closely with data scientists, software engineers, and product managers to develop and implement scalable machine learning solutions that drive business value.

Key Responsibilities :

- Design, develop, and deploy machine learning models and algorithms to solve complex business problems.

- Implement MLOps best practices to ensure robust, scalable, and maintainable machine learning pipelines.

- Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.

- Monitor and optimize the performance of machine learning models in production.

- Develop and maintain automated testing, continuous integration, and continuous deployment (CI/CD) pipelines for machine learning models.

- Ensure data quality and integrity throughout the machine learning lifecycle.

- Stay up-to-date with the latest advancements in machine learning, MLOps, and related technologies.

Qualifications :

- 4+ years of experience in machine learning and data science.

- Proven experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, TFX).

- Strong programming skills in Python and familiarity with machine learning libraries (e.g., TensorFlow, PyTorch, Scikit-learn).

- Experience with cloud platforms (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Docker, Kubernetes).

- Solid understanding of software engineering principles, including version control (e.g., Git), testing, and code reviews.

- Excellent problem-solving skills and the ability to work independently and as part of a team.

- Strong communication skills and the ability to convey complex technical concepts to non-technical stakeholders.

Preferred Qualifications :

- Experience with big data technologies (e.g., Hadoop, Spark).

- Knowledge of data engineering and ETL processes.

- Familiarity with DevOps practices and tools.