ML/AI Engineer- Azure
IndiaRemoteFull-time
AI Summary
Supports Data Science teams by deploying ML models to production, building GenAI/LLM automation, and overseeing ML lifecycle and MLOps practices.
About this role
3
Tasks/ Responsibilities:
- Working with Data Science teams to implement Machine Learning models into production
- Design, delivery GenAI solutions
- Practical and innovative implementations of LLM/ML/AI automation, for scale and efficiency
- Design, delivery and management of industrialized processing pipelines
- Defining and implementing best practices in ML models life cycle and ML operations/LLM operations
- Implementing AI /MLOps/LLMOps frameworks and supporting Data Science teams in best practices
- Gathering and applying knowledge on modern techniques, tools and frameworks in the area of ML Architecture and Operations
- Gathering technical requirements & estimating planned work
- Presenting solutions, concepts and results to internal and external clients
- Creating technical documentation
What We're Looking For:
- At least 5+ years of Data engineering experience with last 3 years experience in building Data processing
- At least 5+ years of experience in production-ready Python code development (e.g., microservices, APIs, etc.)
- At least 3+ years of experience in production-ready ML-related code development
- At least 1+ years of experience with GenAI (ChatGPT, Gemini, RAGs, prompt engineering)
- Practical experience in MLOps/LLMOps tools like AzureML/AzureAI.
-
- Practical experience with Databricks
- Good understanding of ML/AI concepts: types of algorithms, machine learning frameworks, model efficiency metrics, model life-cycle, AI architectures
- Good understanding of Cloud concepts and architectures, as well as working knowledge with selected cloud services, preferably Azure or GCP
- Experience in at least one of following domains: Data Warehouse, Data Lake, Data Integration, Data Governance, Machine Learning, Deep Learning, MLOps
- Practical experience in Spark/PySpark and Hive within Big Data Platforms like Databricks, EMR or similar
- Experience in designing and implementing data pipelines
- Good communication skills
- Ability to work in a team and support others
- Taking responsibility for tasks and deliverables
- Great problem-solving skills and critical thinking
- Fluency in written and spoken English.
What Will Set You Apart:
- Experience in designing, programming ML algorithms, and data processing pipelines using Python
- Good understanding of CI/CD and DevOps concepts, and experience in working with selected tools (preferably GitHub Actions, GitLab, or Azure DevOps)
- Experience in productizing ML solutions using technologies like Spark/Databricks or Docker/Kubernetes.
What we offer:
- Stable employment. On the market since 2008, 1500+ talents currently on board in 7 global sites.
- “Office as an option” model. You can choose to work remotely or in the office, depending on your location.
- Flexibility regarding working hours and your preferred form of contract.
- Comprehensive online onboarding program with a “Buddy” from day 1.
- Cooperation with top-tier engineers and experts.
- Unlimited access to the Udemy learning platform from day 1.
- Certificate training programs. Lingarians earn 500+ technology certificates yearly.
- Upskilling support. Capability development programs, Competency Centers, knowledge sharing sessions, community webinars, 110+ training opportunities yearly.
- Internal Gallup Certified Strengths Coach to support your growth.
- Grow as we grow as a company. 76% of our managers are internal promotions.
- A diverse, inclusive, and values-driven community.
- Autonomy to choose the way you work. We trust your ideas.
- Create our community together. Refer your friends to receive bonuses.
- Activities to support your well-being and health.
- Plenty of opportunities to donate to charities and support the environment.
- Modern office equipment. Purchased for you or available to borrow, depending on your location.
Skills
AzureAIAzure DevOpsAzureMLBig-dataCI/CDCloud (Azure/GCP)DatabricksData GovernanceData LakeData PipelinesData WarehouseDockerETLGenAIGitHub ActionsGitLabHiveKubernetesLLMOpsMicroservicesMLOpsPrompt EngineeringPySparkPythonRAGsREST APISpark
