Act as the overall technical authority for the programme, owning architectural decisions, execution patterns, and technical quality across all workstreams.
Define and enforce standard migration patterns for moving ML workloads from Databricks into AWS SageMaker, while managing exceptions for complex or legacy cases.
Lead and contribute across areas such as AWS SageMaker-based ML execution, Databricks to SageMaker migration, and Python-based ML workloads.
Designing, deploying, and optimizing data-driven machine learning solutions on AWS.
Creating secure and scalable ML systems, enabling effective data management and model deployment.
Leading the enhancement of best practices within the data and ML lifecycle, making a substantial impact across projects and teams.
Jobgether uses an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company.
Support the full operational lifecycle of both traditional machine learning systems and emerging generative AI driven applications.
Enable scalable training, evaluation, deployment, and monitoring for a wide range of ML and GenAI workloads.
Manage model upgrades, framework versions, regression testing, maintenance tasks and maintaining performance across systems and solutions.
Achievers' employee recognition and rewards platform empowers organizations to build cultures where people feel seen and valued, everyday. They're a team of passionate, thoughtful builders with more than 4.3 million users across 190 countries, who care deeply about their product, their customers, and each other.
You own uptime, observability, incident response, and root cause analysis.
Own the AWS architecture.
Make ML pipelines reliable.
Ferra is building AI infrastructure for structural steel estimation. They process large-scale construction drawing PDFs, run computer vision + LLM pipelines, and generate structured steel graphs, takeoffs, and export-ready models. The team is small and technical, which means high ownership, fast decisions, and work has a direct impact on the core product.
Lead a team focused on implementing and maintaining AWS-based data management and execution solutions.
Be responsible for people management, work execution, and representing your team throughout the organization.
Influence the technical roadmap that enables data-driven analytics and machine learning across the enterprise.
Torc is a leader in autonomous driving since 2007 and has spent over a decade commercializing our solutions with experienced partners. Now a part of the Daimler family, we are focused solely on developing software for automated trucks to transform how the world moves freight. Our culture is collaborative, energetic, and team focused.
Design and implement MLOps pipelines to automate model training, deployment, monitoring, and management
Lead/mentor a team of MLOps Engineers, fostering an inclusive and collaborative environment that encourages innovation and continuous learning
Collaborate with Data Scientists and ML Engineers to ensure models are production-ready, scalable, and maintainable
Egen is a fast-growing and entrepreneurial company with a data-first mindset. They bring together the best engineering talent working with the most advanced technology platforms, including Google Cloud and Salesforce, to help clients drive action and impact through data and insights.
Lead our AI & Data department with autonomy as a proactive tech enthusiast.
Develop, train, validate, optimize, and maintain Machine Learning models.
Extract, clean, validate large datasets, and interpret data for business opportunities.
Everfield buys, builds, and grows European vertical market and specialist software companies, providing them with the tools they need to move to the next level. Companies in the Everfield ecosystem follow a decentralised model, maintaining their team, brand, and offices, while focusing on what they do best - building products and supporting customers.
Guide the technical direction of Bondora’s ML engineering stack by selecting, evaluating, and implementing technologies to improve scalability and reliability.
Lead complex, high-risk, or cross-departmental projects that directly influence Data Science delivery, risk model performance, and production stability.
Act as the bridge between Data Science, Data Engineering, and Development to identify and solve systemic technical challenges.
Bondora's mission is to empower people to enjoy life more while alleviating the stress of managing finances. Founded in 2008, Bondora has served over 1 million customers for 16 years and is rapidly growing as a fintech company, set to acquire a banking license and expand investment and loan products across Europe.
Design, implement, and maintain high-performance ML training and inference platforms.
Ship tools that allow any ML engineer to deploy a model in minutes, not days.
Improve scalability, reliability, and cost efficiency of model training and serving systems.
Speechify's mission is to make sure that reading is never a barrier to learning. With nearly 200 people around the globe working in a 100% distributed setting, Speechify's team includes frontend and backend engineers, AI research scientists, and others.
Design and implement data pipelines using Databricks, PySpark, and Delta Lake.
Work closely with business stakeholders and analysts to understand KPIs.
Model and structure data using dimensional modeling techniques.
Clear Tech specializes in Data, Analytics, and Artificial Intelligence, helping companies around the world transform their data into real business value. Our team combines highly skilled talent in Latin America with global best practices across cloud technologies and delivers end-to-end projects.
Design, build, and maintain machine learning model productionization infrastructure.
Streamline model training, validation, and deployment in collaboration with the data science team.
Implement robust monitoring and alerting for model performance, drift, and data quality.
The Athletic delivers in-depth coverage of sports, teams, and athletes. Their newsroom of 500+ full-time staff covers hundreds of professional and college teams across North American markets and football clubs.
Design, implement, and manage AI Platform architecture.
Control AI-related costs, including models, GPUs, and other resources.
Collaborate with ML teams to operationalize AI models and integrate them into systems.
Docplanner empowers patients by giving them access to leave and read reviews about their visit and provides doctors with the technology to manage bookings easily and save time. They are leaders in 13 countries with 2,500+ employees globally and maintain a startup-mindset.
Influence the technical direction for infrastructure and platform capabilities that support our rapidly growing AI product suite.
Architect and evolve our cloud infrastructure (primarily on AWS) to support current and future products.
Mentor and level up engineers across Platform and product teams; review design docs, guide architecture decisions, and model high standards.
Rad AI is on a mission to transform healthcare with artificial intelligence. Our AI-driven solutions are revolutionizing radiology—saving time, reducing burnout, and improving patient care. Rad AI has secured over $140M in funding and our valuation is at $528M.
You will work to build, maintain and improve our Torc ML frameworks.
You have built ML solutions that have reached production.
You want to build, maintain, grow, and improve our ML platform.
Torc has been a leader in autonomous driving since 2007. Now a part of the Daimler family, they are focused solely on developing software for automated trucks to transform how the world moves freight.
Manage machine learning model versioning, lineage tracking, and compliance with governance policies, ensuring reproducibility and secure deployment.
Implement and monitor ML infrastructure, optimizing compute resource allocation across cloud and on-premises environments.
Validation of AI/ML pipelines, ensuring models remain accurate, explainable, and aligned with operational objectives.
SOSi, founded in 1989, is a large private technology and services integrator in the defense and government services industry. They deliver tailored solutions, tested leadership, and trusted results to enable national security missions worldwide.
Define and evolve the technical vision for AI and agentic systems across products.
Design orchestration, data, and serving patterns that handle global scale with reliability.
Collaborate with AI Research to turn prototypes into extensible, governed production frameworks.
KnowBe4 is a cybersecurity company that puts security first, empowering over 70,000 organizations worldwide to strengthen their security culture. They value radical transparency, extreme ownership, and continuous professional development in a welcoming workplace that encourages all employees to be themselves.
Design, develop, and deploy robust ML systems and multi-model AI agents that solve real-world retail challenges.
Lead the entire lifecycle, including prototyping, deployment, monitoring, and maintenance using modern CI/CD and containerisation practices.
Build high-performance data pipelines (ETL/ELT) for both training and real-time inference, ensuring our systems are scalable and reliable.
EDITED is the world’s leading AI-driven retail intelligence platform. They empower the world’s most successful brands and retailers with real-time decision making power. Their environment is dynamic and supportive, encouraging team members to take initiative, innovate, and continuously grow.
Lead customer onboarding and implementation for AISim Physics and ML-based solutions.
Serve as a trusted technical advisor to Product and Engineering teams.
Build and maintain reference architectures, integration patterns, and implementation runbooks.
SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors. At SandboxAQ, they’ve cultivated an environment that encourages creativity, collaboration, and impact.
Partner with teams to co-design scalable solutions.
Lead deployments, considering security and maintainability.
Work with customers to design tailored solutions.
Sama provides high-quality training data that powers AI technology for Fortune 2000 companies. They are experts in data annotation, supporting data for machine learning algorithms and generative AI models and committed to expand opportunities for those who are underprivileged.
Architect, maintain, and scale critical infrastructure.
Ensure system reliability and optimize performance.
Implement modern deployment strategies.
Scribe's Workflow AI platform automatically captures and optimizes workflows so teams work smarter, faster, and more consistently. They are a fast-growing company founded in 2019 with over 5 million users across 600,000 businesses, and they are backed by leading investors.