AI Engineer @ Lingaro
7 dni temu
Stable employment. On the market since 2008, 1300+ talents currently on board in 7 global sites.
“Office as an option” model. You can choose to work remotely or in the office.
Great Place to Work® certified employer.
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+ trainings, 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.
Modern office equipment.
Good understanding of ML/AI concepts: types of algorithms, machine learning frameworks, model efficiency metrics, model life cycle, AI architectures.
Practical experience in Databricks.
Practical experience in MLOps tools like MLFlow, Azure ML, GCP Vertex, AWS Sagemaker.
Good understanding of Cloud concepts and architectures as well as working knowledge with selected cloud services, preferably MS Azure.
Strong experience in at least one of the following domains: Machine Learning, Deep Learning, Data Science, MLOps, GenerativeAI.
Experience in programming ML algorithms and data processing pipelines using Python.
At least 2 years of experience in production ready code development.
Practical skills with scripting languages.
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.
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.
Experience productization ML solutions using technologies like Spark/Databricks or Docker/Kubernetes is a plus.
Good understanding of GenerativeAI and Large Language Models tech stack and concepts (OpenAI, LLM orchestrators - Langchain, Semantic Kernel, etc.) is a plus.
Stable employment. On the market since 2008, 1300+ talents currently on board in 7 global sites.
“Office as an option” model. You can choose to work remotely or in the office.
Great Place to Work® certified employer.
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+ trainings, 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.
Modern office equipment.
,[Building high-performing, scalable, enterprise-grade ML/AI applications in cloud environment. , Working with Data Science teams to implement Machine Learning and statistical models into production. , Practical and innovative implementations of 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. , Implementing AI/MLOps 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: Python, AI, Databricks, Azure ML, Azure, Spark, MLOps, Scala Tools: Agile. Additionally: Sport subscription, Private healthcare, International projects, Free coffee, Modern office, No dress code, In-house trainings.
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