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.
Build and productionize reusable MLOps components supporting scalable and reliable ML workflows.
Establish strong ML lifecycle practices including experiment tracking, evaluation, and reproducibility.
Enable robust and monitored ML systems aligned with healthcare-grade reliability and compliance requirements.
Neko Health aims to shift healthcare from treating illness to preventing it, using advanced, non‑invasive technology and clinical expertise to deliver early, actionable health insights. The company has nearly 100 full-time engineers and supports a flexible workplace that prioritizes work-life balance.
Design and implement tooling that enables researchers to quickly deploy and evaluate new models in production
Design, build, and maintain high-performance, cost-efficient inference pipelines, making architectural decisions about scaling, reliability, and cost trade-offs
Proactively identify and resolve infrastructure bottlenecks, proposing and scoping improvements to iteration speed and production reliability
AssemblyAI builds best-in-class Speech AI models that power the next generation of voice applications. They are a remote team building one of the next great AI companies where teammates define and build their company culture.
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.
CreateFuture is a digital consultancy that builds digital products and services. They have over 500 people and a safe, supportive, and friendly culture.
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.
Own SentiLink’s real-time ML model monitoring domain.
Own our ML experimentation, model tracking, and versioning infrastructure.
Drive improvements to the model development process.
SentiLink provides identity and risk solutions for secure transactions. They are backed by investors like Craft Ventures and Andreessen Horowitz, recognized by Forbes Fintech 50, and have offices across the U.S. and India.
Architect and optimize distributed training and inference systems for large-scale AI models
Design and deliver customer-focused solutions that maximize performance and business value
Lead the transition of ML pipelines from POC to scalable production systems
The company offers an AI-centric cloud platform reshaping the landscape of artificial intelligence. They provide infrastructure, tools, and services for developers to service the explosive growth of the global AI industry, catering to Fortune 1000 companies, startups, and AI researchers.
Manage cloud infrastructure and optimize costs, particularly in AWS environments using Terraform and Python.
Design, develop, and maintain CI/CD pipelines and infrastructure for AI model training and deployment.
Ensure platform scalability and efficient resource utilization.
NEORIS, now part of EPAM Systems, is a Digital Accelerator that helps companies step into the future. With more than 20 years of experience as Digital Partners to some of the world’s leading organizations, they are over 4,000 professionals across 11 countries and foster a multicultural, startup-minded culture that promotes innovation, continuous learning, and the delivery of high-impact solutions for their clients.
Own model serving: Design, build, and maintain low-latency, highly-available serving stacks for in-house ML model serving and integrating with LLM serving partners.
Automate training pipelines: Orchestrate data prep, training, evaluation, and registry workflows on Kubernetes with solid MLOps practices.
Optimize at scale: Profile and tune throughput, memory, and cost; introduce caching, sharding, batching, and GPU/CPU autoscaling where it pays off.
Cresta aims to turn every customer conversation into a competitive advantage by unlocking the true potential of the contact center. Their platform combines AI and human intelligence to help contact centers discover customer insights and automate conversations.
Designing, architecting, and implementing modern, secure Azure AI platforms.
Enabling Data Science teams by building the "paved road" for deploying Azure ML Workspaces and GenAI services.
Automating model retraining, versioning, and deployment to inference endpoints using Azure DevOps.
Nordcloud is a European leader in cloud implementation, application development, managed services and training. It is a recognized cloud-native pioneer with over 1,300 employees and has delivered over 1,000 successful cloud projects for companies ranging from midsize to large corporates. Nordcloud values diversity and is dedicated to providing equal opportunities for all candidates and employees.
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.
Scale the decisionmaking process for tools for the tvScientific AI team, from our workflows to our training infrastructure to our Kubernetes deployments
Improve the developer experience for the data science team
Upgrade our observability tooling
tvScientific is the first and only CTV advertising platform purpose-built for performance marketers. They leverage massive data and cutting-edge science to automate and optimize TV advertising to drive business outcomes. An Idealab company, tvScientific was co-founded by executives with deep roots in programmatic advertising and digital media.
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.
Architect, implement, and maintain production-grade, low-latency ML services.
Collaborate with data scientists, product managers, and engineers.
Design and support experimentation frameworks to test hypotheses and measure improvements.
Smart Working connects skilled professionals with global teams and products for full-time, long-term roles. They are one of the highest-rated workplaces on Glassdoor and value integrity, excellence, and ambition for their employees' personal and professional growth.
Partner with stakeholders to tackle technical problems at scale, building framework agnostic services.
Establish roadmap and architecture for Wealthsimple’s Machine Learning platform.
Build highly performant scalable systems, contributing to our ML platform on Kubernetes, Bedrock and Sagemaker.
Wealthsimple aims to provide financial freedom by making financial services transparent and low-cost. As the largest fintech company in Canada, with over 1,500 employees, they manage over $100 billion in assets and foster a collaborative and quality-focused culture.
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.
Design, develop, and maintain high-performance, scalable, and secure backend services, primarily using Python and frameworks like FastAPI
Translate ambiguous business and technical requirements into concrete software designs and actionable tasks for cross-functional teams
Operate and maintain production applications at scale, ensuring high availability, performance, and reliability
SmartAsset is an online destination for consumer-focused financial information and advice, whose mission is helping people make smart financial decisions, reaching over an estimated 59 million people each month. Valued at over $1 billion, SmartAsset has earned recognition on the Inc. 5000 and Deloitte Technology Fast 500 lists.
Design and own CI/CD pipelines for ML/AI workflows.
Build and maintain scalable ML/AI infrastructure on cloud platforms.
Equip is a virtual, evidence-based eating disorder treatment program. They aim to ensure everyone can access effective treatment, operating in all 50 states and partnering with major health insurance plans, recognized for its engaged culture and sustainable treatment.
Lead and manage a team of ML engineers, scientists, and researchers, fostering mentorship, development, and retention.
Execute the machine learning roadmap, focusing on 3D deep learning, computer vision, and generative AI applications.
Partner with product, engineering, and research stakeholders to align technical strategy with business objectives.
Jobgether is using an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. They appreciate your interest and wish you the best!
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.