Lingaro Group | Careers

ML/AI Engineer with GCP/ Azure

Written by it | Dec 6, 2024 2:55:19 PM

About DS/AI Competency Center:

Focuses on leveraging data, analytics, and artificial intelligence (AI) technologies to extract insights, build predictive models, and develop AI powered solutions. Utilizes Exploratory Data Analysis, Statistical Modeling and Machine Learning, Model Deployment, and Integration as well as Model Monitoring and Maintenance. Delivers business solutions using multiple AI techniques and tools.

Tasks:

The person we are looking for will become part of Data Science and AI Competency Center working in AI Engineering team.

  • Working with Data Science teams to implement Machine Learning models into production
  • 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

Must Have:

  • 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
  • Practical experience in MLOps/LLMOps tools like AzureML/AzureAI or GCP VertexAI
  • 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.

Nice to have:

  • 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.

Why join us: 

  • Stable employment. On the market since 2008, 1300+ talents currently on board in 7 global sites.
  • 100% remote.
  • Flexibility regarding working hours.
  • Full-time position
  • 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.
  • 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.