Tasks:
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Building high-performing, scalable, enterprise-grade ML/AI applications in cloud environment.
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Working with Data Science teams to implement Machine Learning and statistical models into production.
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Practical and innovative implementations of ML/AI automation, for scale and efficiency.
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Design, delivery and management of industrialized processing pipelines.
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Defining and implementing best practices in ML models life cycle and ML operations.
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Implementing AI/MLOps frameworks and supporting Data Science teams in best practices.
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Gathering and applying knowledge on modern techniques, tools and frameworks in the area of ML Architecture and Operations.
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Gathering technical requirements & estimating planned work.
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Presenting solutions, concepts and results to internal and external clients.
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Creating technical documentation.
Requirements:
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Good understanding of ML/AI concepts: types of algorithms, machine learning frameworks, model efficiency metrics, model life cycle, AI architectures.
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Practical experience in MLOps tools like MLFlow, Azure ML, GCP Vertex, AWS Sagemaker.
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Good understanding of Cloud concepts and architectures as well as working knowledge with selected cloud services, preferably MS Azure.
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Strong experience in at least one of the following domains: Machine Learning, Deep Learning, Data Science, MLOps, GenerativeAI.
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Experience in programming ML algorithms and data processing pipelines using Python.
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At least 2 years of experience in production ready code development.
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Practical skills with scripting languages.
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Experience in designing and implementing data pipelines.
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Good communication skills.
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Ability to work in a team and support others.
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Taking responsibility for tasks and deliverables.
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Great problem-solving skills and critical thinking.
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Fluency in written and spoken English.
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Good understanding of CI/CD and DevOps concepts, and experience in working with selected tools (preferably GitHub Actions, GitLab or Azure DevOps) is a plus.
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Experience productization ML solutions using technologies like Spark/Databricks or Docker/Kubernetes is a plus.
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Good understanding of GenerativeAI and Large Language Models tech stack and concepts (OpenAI, LLM orchestrators - Langchain, Semantic Kernel, etc.) is a plus.
We offer:
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Stable employment. On the market since 2008, 1300+ talents currently on board in 7 global sites.
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“Office as an option” model. You can choose to work remotely or in the office.
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Great Place to Work® certified employer.
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Flexibility regarding working hours and your preferred form of contract.
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Comprehensive online onboarding program with a “Buddy” from day 1.
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Cooperation with top-tier engineers and experts.
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Unlimited access to the Udemy learning platform from day 1.
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Certificate training programs. Lingarians earn 500+ technology certificates yearly.
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Upskilling support. Capability development programs, Competency Centers, knowledge sharing sessions, community webinars, 110+ training opportunities yearly.
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Grow as we grow as a company. 76% of our managers are internal promotions.
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A diverse, inclusive, and values-driven community.
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Autonomy to choose the way you work. We trust your ideas.
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Create our community together. Refer your friends to receive bonuses.
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Activities to support your well-being and health.
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Plenty of opportunities to donate to charities and support the environment.
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Modern office equipment. Purchased for you or available to borrow, depending on your location.