Source Job

• Deploy and optimize ML/LLM models on platforms like NVIDIA Triton and vLLM within Kubernetes clusters.
• Integrate models with Rackspace’s Unified Inference API and API Gateway for multi-tenant routing.
• Configure telemetry for GPU utilization, request tracing, and error monitoring.

We combine our expertise with the world’s leading technologies — across applications, data and security — to deliver end-to-end solutions.

Lead AI and ML initiatives to design and implement production-grade machine learning systems and pipelines. Develop scalable infrastructure for model training, evaluation, and deployment, ensuring reliability and observability. Collaborate with cross-functional teams to drive innovation and efficiency.

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

• Design, build, and deploy machine learning models for personalization, automation, and insights.
• Manage the full ML lifecycle: data preprocessing, feature engineering, training, tuning, evaluation, deployment.
• Integrate ML outputs into user-facing products and backend systems.

BJAK is a leading digital insurance platform, helping millions of users access affordable and transparent financial protection.

Deploy and monitor machine learning models in production using tools like Docker, Kubernetes, and MLflow to ensure scalability and reliability. Build and maintain data pipelines using Airflow, Spark, or Kafka to support model training and inference. Integrate ML models into business applications, collaborating with software engineers to operationalize solutions.

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

• Lead the design and deployment of advanced AI inference systems for high-profile clients.
• Translate complex business problems into robust, real-time AI architectures.
• Partner with technical teams and clients to deliver scalable, high-performance solutions on modern GPU and cloud infrastructure.

Jobgether uses an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against a role's core requirements.

• Help define the direction for the team.
• Define and prioritize ML Platform initiatives.
• Enable teams to build features at scale by providing a foundation of reusable software components and infrastructure.

Motive empowers the people who run physical operations with tools to make their work safer, more productive, and more profitable. Motive serves nearly 100,000 customers – from Fortune 500 enterprises to small businesses – across a wide range of industries.

• Design, build, and optimize high-performance systems in Python supporting AI data pipelines and evaluation workflows
• Develop full-stack tooling and backend services for large-scale data annotation , validation, and quality control
• Improve reliability, performance, and safety across existing Python codebases

Alignerr connects top technical experts with leading AI labs to build, evaluate, and improve next-generation models. They work on real production systems and high-impact research workflows across data, tooling, and infrastructure.

As a Senior MLE, debug complex AI implementations and optimize inference performance. Work directly with product teams building solutions and develop blueprints for proven patterns. Operate in a high-velocity environment where priorities shift rapidly based on team needs.

Join the team redefining how the world experiences design.

• Invent and prototype new model architectures that optimize inference speed, including on edge devices.
• Build and maintain evaluation suites for multimodal performance across a range of public and internal tasks.
• Collaborate with the data and infrastructure teams to build scalable pipelines for ingesting and preprocessing large audio datasets.

Liquid AI, spun out of MIT, aims to build efficient AI systems at every scale, creating Liquid Foundation Models that operate on-device and under real-time constraints.

• Design and implement Python services for real-time fraud detection and compliance monitoring.
• Build scalable data pipelines for feature building and model training.
• Develop and operate a developer-friendly ML platform with automated quality checks.

Kraken is a mission-focused company rooted in crypto values, aiming to accelerate the global adoption of crypto for financial freedom and inclusion.

• Design scalable, future-proof data platforms optimized for AI research workloads.
• Build efficient self-serve data processing pipelines leveraging GCP's advanced services.
• Implement guardrails for cost, quality, and performance.

AssemblyAI is at the forefront of Speech AI, creating powerful models for speech-to-text and speech understanding via an API. They're a remote team of startup veterans and AI researchers looking to build one of the next great AI companies.

Build backend and pipeline systems that turn models into real search experiences for 110M+ daily users, owning data flows, ranking and retrieval services, and low-latency model-serving APIs. Integrate models into production through robust interfaces and DAGs, enabling fast iteration and powering discovery across the internet’s largest community platform. Ensure pipelines and systems support high scale, low latency, and operational excellence.

Reddit is a community of communities built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet.

• Design, implement, and deploy AI-powered features, including model training, fine-tuning, and prompt engineering workflows.
• Translate product requirements into robust, production-ready AI solutions, working with Product Managers, Software Engineers, and Data Scientists.
• Optimize models and infrastructure for scalability, latency, and cost efficiency, partnering with DevOps and MLOps to ensure reliable and maintainable AI pipelines.

Paper is reimagining how schools support students so that every learner can reach their full potential.

Combine Software Engineering and Data Science disciplines to create production-ready Machine Learning models. Develop frameworks and platform to build, deploy, serve and monitor ML-based services. Contribute to vision and architecture to scale ML solutions at QuintoAndar's business.

We are Grupo QuintoAndar, the largest real estate ecosystem in Latin America, guided by a shared purpose of helping people love the place they live.

• Design and deliver advanced solutions that generate predictions from a wide range of Computer Vision models.
• Build and evolve key components of the Roboflow Platform to ensure seamless, reliable model deployment at scale.
• Contribute to and maintain Roboflow’s open-source projects, helping grow and support the broader developer community.

Roboflow simplifies building and using computer vision models, and over 1M+ developers, including those from half the Fortune 100, use Roboflow’s tools.

• Build, maintain and improve Torc ML frameworks.
• Use Terraform, AWS Managed Services, EKS, Ray.
• Focus on data ops, ML development pipeline, logging & aggregation.

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. Their culture is collaborative, energetic, and team focused.

• Build and deploy ML models serving 100M+ predictions per day to personalize user experiences at scale.
• Design ranking algorithms that balance relevance, diversity, and revenue.
• Run statistically rigorous A/B tests to measure true business impact.

Launch Potato is a profitable digital media company that reaches over 30M+ monthly visitors through brands such as FinanceBuzz, All About Cookies, and OnlyInYourState.

• Build and deploy AI-driven products that accelerate clinical trials and improve patient outcomes.
• Develop advanced ML models and LLM-powered agents for critical use cases like patient recruitment, enrollment forecasting, and study feasibility.
• Leverage modern cloud tools and MLOps best practices to build robust data pipelines and deploy models at scale.

At OneStudyTeam (a Reify Health company), we specialize in speeding up clinical trials and increasing the chance of new therapies being approved with the ultimate goal of improving patient outcomes.

• Build and design end-to-end training pipelines for AI models, covering data ingestion to inference.
• Architect scalable inference systems using tools like vLLM, TensorRT-LLM, or DeepSpeed.
• Shape early product direction by experimenting with new use cases and building AI-powered experiences.

A1 is a self-funded, independent AI group backed by BJAK, focused on building a new consumer AI product with global impact.

• Lead development stages for AI/ML projects from exploration to maintenance.
• Design and implement scalable ML pipelines for large datasets with data scientists and network security experts.
• Conduct experiments and analyze results using metrics and visualization techniques.

Corelight is a cybersecurity company that transforms network and cloud activity into evidence for elite defenders. Fueled by accelerating revenue and investments from top-tier venture capital organizations, they are rapidly expanding their team with a geographically dispersed yet connected employee base.