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Job Title: Machine Learning, Data Engineering, MLOps Engineer
Reference: RFQ SMART7748_HM
Years of Experience: 5 to 7 Years
Mandatory Skills:
1. 5?7 years of professional experience in Machine Learning Engineering, MLOps, Data Engineering, or Software Engineering.
2. Experience with big data technologies such as Apache Spark, Kafka, Hadoop, Flink, or similar distributed systems.
3. Strong experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
4. Experience developing and maintaining large-scale data engineering pipelines using Python, Spark, Databricks, Airflow, or similar technologies.
5. Experience implementing CI/CD pipelines using Azure DevOps, GitHub Actions, Jenkins, or equivalent tools.
6. Strong proficiency in Docker, Kubernetes, and container-based application deployment.
7. Strong understanding of software engineering best practices including object-oriented design, design patterns, version control, testing strategies, code reviews, and secure development practices.
8. Experience with model lifecycle management, experiment tracking, feature management, and production model deployment.
9. Strong understanding of data governance, security, and compliance requirements in enterprise environments.
10. Excellent analytical, problem-solving, collaboration, and communication skills.
11. Ability to manage multiple projects and priorities in a fast-paced environment.
Desired Expertise (in one or more of the following areas):
1. Professional certifications in Machine Learning, Cloud Technologies, Data Engineering, or MLOps.Hands-on experience with Databricks, Snowflake, Delta Lake, Feature Stores, or Vector Databases.
2. Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn, MLflow, or equivalent platforms.
3. Experience building Generative AI, LLM, RAG, Agentic AI, or NLP-based solutions.
Familiarity with Infrastructure as Code tools such as Terraform, Bicep, or CloudFormation.
4. Experience with monitoring, observability, and logging platforms such as Grafana, Prometheus, ELK, Azure Monitor, or Datadog.
5. Experience working in Agile/Scrum development environments.
6. Experience mentoring junior engineers and leading technical initiatives across teams.
Educational Qualification
Bachelor?s or Master?s degree in Computer Science, Software Engineering, Data Science, Artificial Intelligence, or related field.
Work arrangement
No
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