ML Engineer Senior - GenAI Solutions

In this role you will advance Generative AI initiatives alongside experienced data professionals. You will apply hands‑on GenAI capabilities across cloud and on‑prem architectures, building scalable data pipelines and production ML solutions. You’ll lead ML engineers, collaborate with stakeholders, and translate business opportunities into measurable AI impact. You will shape deployment strategies, MLOps practices, and cross‑functional delivery at scale in a dynamic, global team.Benefits

• Apply Generative AI capabilities across Azure/GCP and on‑prem GenAI architectures and MLOps
• Develop, validate and implement ML models at scale
• Design and build data pipelines from experiments to production
• Identify business opportunities and translate them into AI initiatives
• Lead ML engineers and manage multiple projects
• Engage with stakeholders to align AI solutions with business goals

• At least 5 years of production experience in Data Science or Software Engineering
• Strong background in mathematics, probability, statistics and algorithms
• Minimum 6–12 months of Generative AI deployment experience
• Knowledge of vector databases is beneficial
• Understanding of data structures, data modeling and software architecture
• Proficiency in at least two mainstream programming languages (Python, Scala, Java, C++)
• Experience building infrastructure for technical users (DS, ML practitioners, data consumers/producers)
• Solid knowledge of Spark and Databricks is a strong plus
• Experience deploying ML solutions on public cloud platforms with cross‑cloud capabilities; Snowflake knowledge is a plus
• Deep knowledge of ML frameworks (Keras, PyTorch)
• Ability to design and implement production ML pipelinesExperience with deployment including CI/CD, containerization, and MLops concepts
• Ability to mentor junior team members
• Strong relationship‑building with internal teams and external clients