What you will do

Be a key member of a growing team (data scientists, data engineers, DevOps engineers) that designs and implements artificial intelligence solutions in a production environment, leveraging a variety of AI tools and machine learning algorithms
Design, build, maintain and deploy the infrastructure for AI-based solutions
Integrate solutions with existing systems and application. Responsible for MLOps and DevOps to ensure scalability, reliability, and security of these systems
Implement automation tools and processes for NLP, GenAI, model training, testing, and deployment
Build tools and capabilities for model management and model performance monitoring
Collaborate effectively with the team and across cross-functional stakeholders
Model a high-performance culture with critical thinking, problem-solving, learning, collaboration, and experimentation within the team

What you will bring

Bachelor's degree completed in Computer Science or a related field
3+ years of experience with AI, software engineering, MLOps, DevOps, or data engineering, in a skilled role




Experience with document intelligence, generative AI, agentic AI, automation, NLP and machine learning
Experience with Azure DevOps, CI/CD, Terraform, Python and other scripting languages
Experience with integrating DevSecOps practices and principles throughout the project life cycle
Experience with Big Data technologies, cloud-based analytics, non-relational datastores, data visualization tools, and open-source tools for data processing
Experience with Agile methodologies (Scrum, Kanban) and project management tools such as Jira.
Travel required: Minimal (a couple of times a year)

What we would like to see

Experience with Databricks and Azure cloud platforms, machine learning services, and best practices
Experience in open-source AI/ML tools, frameworks technologies (for example, Meta, HuggingFace, Nemo, TensorFlow, PyTorch, scikit-learn, Apache MXnet, Spark MLlib, etc.)
Experience with predic

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