Tasks:
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Building high-performing, scalable, enterprise-grade LLM/AI applications in cloud environment
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Working with Data Science teams to analyze requirements, build architecture conceptions, lead a implementation GenerativeAI and Machine Learning models into production (Tech Lead)
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Practical and innovative implementations of LLM/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 GenAI/ML models life cycle and ML operations/LLM operations
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Implementing AI /MLOps/LLMOps 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 including diagrams
Requirements:
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At least 8+ years of experience in production-ready Python code development (e.g., microservices, APIs, etc.)
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At least 8+ years of experience in production-ready ML-related code development
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At least 2 years of experience in production-ready LLM-related code development, preferably based on the Retrieval Augmented Generation concept (RAG)
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At least 3+ years of experience in Cloud Architecture
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Good understanding and experience with GenerativeAI models APIs (Large Language Models/Large Multimodal Models)
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Good understanding and experience with LLM orchestrators (e.g., Langchain, etc.) and concepts (RAG, in-context learning, fine-tuning)
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Good understanding of LLM evaluators, validators, and guardrails
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Good understanding of LLMOps concepts like GenAI operationalization\scaling (e.g., LLMs serving, performance & API Gateways, LLMs tracking & monitoring)
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Experience in developing GenAI apps in rapid frameworks (e.g., Streamlit)
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Experience in MLOps/LLMOps tools like AzureML/AzureAI or GCP VertexAI
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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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Good understanding of Cloud concepts and architectures, as well as working knowledge with selected cloud services, preferably Azure or GCP
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UML notation
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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.
Nice to have skills & knowledge:
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Experience in designing, programming ML algorithms, and data processing pipelines using Python
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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)
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Experience in productizing ML solutions using technologies like Spark/Databricks or Docker/Kubernetes.
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BPMN, Archimate
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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Internal Gallup Certified Strengths Coach to support your growth.
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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.