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.
Design, develop, and deploy AI/ML models and pipelines that meet mission and performance objectives.
Build, train, and fine-tune models using frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, and LangChain.
Write clean, efficient Python code for data ingestion, feature engineering, embeddings, and inference services.
Frontier Technology Inc. (FTI) delivers mission-focused solutions to the Department of Defense (DoD/DoW) and Intelligence Community (IC) through advanced engineering, digital transformation, and program execution expertise. They help their customers solve complex challenges and achieve mission success by integrating people, process, and technology.
Work side by side with clients, PMs, and Architects to scope and deploy AI systems.
Build and integrate systems using LLMs, RAG pipelines, agent frameworks, vector databases and related tools.
Debug relentlessly and optimize for reliability in production, not just elegance in code.
Jobgether uses an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Their system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company.
Implement production AI / ML workloads using Ray and Anyscale.
Advise customers on ML system architecture.
Partner with customer MLE and MLOps teams to integrate Ray into existing platforms and workflows.
Anyscale is on a mission to democratize distributed computing and make it accessible to software developers. They are commercializing Ray, an open-source project creating an ecosystem of libraries for scalable machine learning and are backed by Andreessen Horowitz, NEA, and Addition.
Prototype new training frameworks and production-ize solutions at scale.
Design, optimize and test model integration infrastructure.
Clarifai is a leading, full-lifecycle deep learning AI platform for computer vision, natural language processing, LLM's and audio recognition. Clarifai was founded in 2013 and has employees remotely based throughout the United States, Canada, Argentina, India and Estonia.
Strong computer science or engineering background with 3+ years of coding experience with Python.
Advanced knowledge of AWS services including but not limited to their ML services (AWS SageMaker and AWS Step Functions).
Experience with ML monitoring and automation tools (MLflow, SagaMaker Pipelines).
Bluelight is a leading software consultancy dedicated to designing and developing innovative technology that enhances users' lives. With a presence across the United States and Central/South America, Bluelight is in an exciting phase of expansion, continually seeking exceptional talent to join its dynamic and diverse community.
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.
Work with research teams to design and build our training infrastructure
Prototype new training frameworks and production-ize solutions at scale
Design, optimize and test model integration infrastructure
Clarifai is a leading AI platform specializing in computer vision, NLP, LLMs, and audio recognition, helping organizations transform unstructured data into structured data. Founded in 2013, they remotely operate across multiple countries with backing from industry leaders, fostering a diverse and equal opportunity workplace.
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.
Elevate Retail with AI-Driven Solutions to transform retail strategy with our AI-powered platform, designed to curate the finest deals and streamline product discovery for consumers.
Empower global marketing efforts with automation and personalised content that resonates with shoppers.
Autonomy to work on data pipelines, writing SQL queries and processing data using Pandas, Polars or Spark..
ShopFully is the platform turning browsing into shopping, connecting 200 million shoppers with deals while boosting local sales for retailers and brands. They are a team of 450 people from 30 different nationalities, innovating and building a more diverse team.
Build end-to-end training pipelines: data → training → eval → inference
Design new model architectures or adapt open-source frontier models
Fine-tune models using state-of-the-art methods (LoRA/QLoRA, SFT, DPO, distillation)
A1 is a self-funded AI group operating in full stealth, building a new global consumer AI application focused on an important but underexplored use case. They are assembling a small, elite team of ML and engineering builders who want to work on meaningful, high-impact problems.
Design, build, and scale enterprise-grade AI/ML systems that power internal workflows and external-facing AI/ML platforms.
Develop a production-ready Generative AI and MLOps platform with reusable components used to deploy multiple AI solutions across Natera’s business units.
Implement cloud-native infrastructure for large-scale model training and serving using Kubernetes, MLflow, Terraform, and AWS-native services
Natera is a global leader in cell-free DNA (cfDNA) testing. They are dedicated to oncology, women’s health, and organ health, aiming to make personalized genetic testing and diagnostics part of the standard of care. The Natera team consists of highly dedicated statisticians, geneticists, doctors, laboratory scientists, business professionals, software engineers and many other professionals from world-class institutions.
Design, build, and operate customer-facing features integrated into core product workflows.
Build and maintain internal services that provide stable, reusable interfaces for other engineers.
Bring AI workflows to production with observability, fallback strategies, and consideration for cost.
Turquoise Health aims to simplify healthcare pricing, increase transparency, and lower costs. They are a Series B startup backed by top VCs with a passion for improving healthcare and a team of ambitious and well-rounded individuals.
Act as a solution expert across ML domains including evaluations, training, inference, data pipelines, quality, and optimisation.
Work directly alongside product teams as a trusted partner, helping them navigate technical challenges and arrive at effective solutions.
Develop blueprints, patterns, and paved roads that allow other teams to follow proven approaches and accelerate their own implementations.
Canva is a design platform that enables users to create professional designs. They have a flagship campus in Sydney, a second campus in Melbourne, and co-working spaces in other locations, with a flexible work environment.
Build decisioning and optimisation models for Canva’s payments platform.
Define the ML strategy and operating model for payments optimisation.
Work with engineering, data, fraud, and product teams to improve revenue outcomes.
Canva is redefining how the world experiences design. They have campuses in Sydney and Melbourne plus co-working spaces in other cities, and offer flexible work arrangements to empower their team.
Lead the design, development, and deployment of AI/ML-powered solutions tailored to customer needs.
Architect and implement robust application integrations using Python, JavaScript, or similar languages.
Drive data-driven solution development by analyzing complex datasets to extract insights and inform product direction.
Atlassian aims to unleash the potential of every team through its software products designed for all types of work. They value the unique contributions of all Atlassians and do not discriminate based on various factors, ensuring an inclusive culture.
Collaborate with cross-functional teams to improve scalable AI systems.
Research, evaluate, and integrate new AI technologies for payment systems.
Build and deploy AI solutions using Python, LLM libraries, AI services, and AWS.
DLocal enables companies to collect payments in 40 emerging market countries, helping global brands increase conversion rates and simplify payment expansion. They have 1000+ teammates from 30+ different nationalities and offer a flexible, remote-first dynamic culture.
Design and implement AI-powered features end to end, including prompts, agents, tools, retrieval, evaluation, and feedback loops.
Build agent systems that interact safely with infrastructure, codebases, and deployment pipelines.
Integrate LLMs deeply into product workflows as core platform primitives.
SuperPlane is an AI-native DevOps control plane with a mission to build the platform teams use to ship and manage software in the AI era. They are a fast-moving company aiming high, rethinking DevOps from first principles for the AI era to create a single control layer for engineers and agents to collaborate safely.