9 open jobs on The Stack list MLflow as a key skill. They come from 7 companies in 4 countries, and 9 offer visa sponsorship. All were posted in the last 60 days.
This page lists jobs whose listing names MLflow in its key skills. We do not guess skills from the job title.
What you'll do: Define model development methodologies and best practices across the lifecycle; support productionization of Oracles that pilot Prima's microservices; develop tools, packages, microservices, and data pipelines to enable team goals.
What they ask for: Proficient Python programming; experience bringing ML models to production; strong software development practices (TDD/BDD); solid software architecture and ability to work in English.
What you'll do: Define model development methodologies and lifecycle, leading in technology stack choices. Productionize ML components (Oracles) that drive Prima's microservices. Build tools, pipelines, and platforms to accelerate ML and software…
What they ask for: Strong Python programming and hands-on experience with the ML model lifecycle from development to production. Proficiency in software engineering practices (TDD/BDD) and software architecture. Nice-to-have experience with…
What you'll do: Design and implement scalable ETL/ELT data pipelines and Lakehouse architectures on Databricks, integrating batch and streaming sources. Optimize data models (Delta Lake, medallion architecture), enable governed data products, and…
What they ask for: Minimum 5–8 years in data engineering or data architecture with at least 3+ years on Databricks, a university degree, strong SQL and Python skills, and hands-on experience with cloud platforms (AWS/Azure/GCP). Familiarity with Databricks…
What you'll do: Lead engineering squads delivering complex AI-driven systems, shaping architecture and delivery strategy, and guiding Proofs of Concepts. Stay hands-on with engineering about 60% of time, building POCs, solving difficult problems, and…
What they ask for: Strong experience in software engineering, technical delivery, or technical leadership; track record deploying ML systems to production (serving, monitoring, retraining); experience mentoring teams; hands-on with PyTorch; familiarity with…
What you'll do: Apply data science, machine learning and AI techniques to transform complex datasets into actionable insights and predictive models; develop, evaluate and operationalise analytical models and AI-driven solutions; collaborate with…
What they ask for: Experience applying data science, AI or advanced analytics to real-world problems, strong analytical and communication skills, and ability to work in multidisciplinary teams. Candidates must be able to obtain and maintain (or already hold)…
What you'll do: Design and build real-time machine learning services for ads monetization and in-game personalization. Manage data pipelines, model deployment, and production monitoring in collaboration with data scientists.
What they ask for: Requires strong experience in Python, SQL, and MLOps for production-grade systems. Candidates must be able to work effectively with data scientists and possess strong communication skills in English and Russian.
What you'll do: Build a scalable, declarative ML lifecycle platform for financial crime detection, including training pipelines, model packaging and serving, evaluation, monitoring, and audit trails. Integrate FinCrime-specific tooling with Wise’s central…
What they ask for: Candidates need production experience building ML platform infrastructure and strong software engineering skills, including Python, Kotlin or Java, and SQL. They should understand the end-to-end ML lifecycle and have experience with…
What you'll do: You will own the analytical and machine learning lifecycle, from data exploration and feature engineering to developing and deploying production-level models. Additionally, you will collaborate with cross-functional teams to translate…
What they ask for: The ideal candidate has 3–5 years of professional experience in data science and strong proficiency in Python, machine learning, and statistical methods. A degree in Mathematics, Computer Science, or a related field is required, along with…
What you'll do: You will own the analytical and machine learning lifecycle, from data exploration and feature engineering to developing and supporting production-level models. Additionally, you will collaborate with cross-functional teams to translate…
What they ask for: The ideal candidate has 3–5 years of professional experience in data science and a degree in a quantitative field. You must possess strong proficiency in Python, SQL, and machine learning, along with the ability to communicate technical…
