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:
- Building high-performing, scalable, enterprise-grade LLM/AI applications in cloud environment
- Working with Data Science teams to implement GenerativeAI and 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 GenAI/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
Requirements:
- At least 3+ years of experience in production-ready Python code development (e.g., microservices, APIs, etc.)
- At least 2+ years of experience in production-ready ML-related code development
- At least 1+ years of experience in production-ready LLM-related code development, preferably based on the Retrieval Augmented Generation concept (RAG)
- Good understanding and experience with GenerativeAI models APIs (Large Language Models/Large Multimodal Models)
- Good understanding and experience with LLM orchestrators (e.g., Langchain, etc.) and concepts (RAG, in-context learning, fine-tuning)
- Good understanding of LLM evaluators, validators, and guardrails
- Good understanding of LLMOps concepts like GenAI operationalization\scaling (e.g., LLMs serving, performance & API Gateways, LLMs tracking & monitoring)
- Experience in developing GenAI apps in rapid frameworks (e.g., Streamlit)
- Experience in MLOps/LLMOps tools like AzureML/AzureAI or GCP VertexAI
- 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
- 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.