8 open jobs on The Stack list Production deployment as a key skill. They come from 7 companies in 3 countries, and 8 offer visa sponsorship. All were posted in the last 60 days.
This page lists jobs whose listing names Production deployment in its key skills. We do not guess skills from the job title.
What you'll do: Design, develop, and optimize ML models for mobile app features; deploy and monitor models in production; collaborate with cross-functional teams to integrate AI-driven solutions.
What they ask for: Around 4+ years in AI/ML for mobile applications; proficient in Python and ML frameworks (TensorFlow, PyTorch); experience with deep learning, NLP, computer vision, and cloud ML services; strong software engineering practices and ability…
What you'll do: Solve a scaling bottleneck in a critical service, deploy new features to production with feature flags, investigate and fix production issues, and design scalable architectures for higher traffic.
What they ask for: Significant experience in backend programming languages, ability to design architecture for high-scale systems, and a degree (BS/MS/PhD) or equivalent experience, with an interest in applying AI tools to development.
What you'll do: Build, validate and monitor credit scorecards and decisioning rules using bureau, Open Banking and internal data. Design and test credit strategies, pricing tiers and limits, balancing risk, volume and margin; work with engineers to deploy…
What they ask for: 2-5 years in decision science or data science within consumer lending or regulated financial services; experience developing credit scorecards or risk models (logistic regression or gradient boosting); strong SQL skills; understanding of…
What you'll do: Lead the team in iterating on L2 driving performance by diagnosing on-road issues and resolving them through data and model architecture changes. You will balance hands-on technical development with team leadership to scale the driving…
What they ask for: You must be highly technical with hands-on experience in Python and delivering production-grade machine learning models, preferably in robotics or autonomous vehicles. The role requires a strong focus on production-level iteration and the…
What you'll do: Provide technical leadership for data science within the Claims department, focusing on fraud detection and risk decisioning. Design and deploy production-grade machine learning and Generative AI systems to automate and improve the claims…
What they ask for: Requires significant commercial experience in end-to-end machine learning and hands-on experience shipping Generative AI systems in production. Candidates must possess a strong statistical foundation and the ability to influence technical…
What you'll do: Provide technical leadership for data science in claims and fraud, focusing on scaling decisioning and automating the claims journey. Design and deploy production-grade machine learning and generative AI systems while collaborating with…
What they ask for: Requires significant commercial experience in end-to-end machine learning and hands-on experience shipping generative AI systems in production. Candidates must possess a strong statistical foundation and proven ability to influence…
What you'll do: You will build and deploy agentic AI automations to optimize claims handling processes directly into production. You will work closely with claims handlers and operations teams to identify inefficiencies and implement scalable, reliable…
What they ask for: The role requires a strong background in product engineering or AI/ML with the ability to own features from conception to production. Candidates must demonstrate a deep understanding of agentic AI systems and a proactive, hands-on approach…
What you'll do: You will take full ownership of building and scaling agentic AI systems, including retrieval pipelines and LLM orchestration. Additionally, you will design automated evaluation frameworks and ensure seamless integration of AI…
What they ask for: Candidates must have a proven track record of deploying complex LLM-driven systems in production environments. Expert-level proficiency in Python and experience with data architectures for unstructured information are mandatory.
