Freelance Machine Learning Engineer

Cresta is dedicated to transforming every customer interaction into a strategic advantage by harnessing the full potential of the contact center. Our innovative platform merges advanced AI with human insight to empower contact centers to unveil customer insights, optimize behavioral practices, automate conversations, and streamline inefficient processes, ena…

Join Upwork Inc., a global leader in connecting businesses with AI-enabled talent, as a Senior Lead Machine Learning Engineer. In this pivotal role, you will architect and scale the future of agentic intelligence, leading the end-to-end development of AI agents and their underlying platform. From training and evaluating large language models to ensuring runtime orchestration and safety, you will drive innovative solutions that empower both internal teams and external developers to create reliable and high-performing AI agents. This hands-on position blends applied research with platform engineering, making a significant impact on Upwork's mission to transform the workforce for the age of AI.

Wisedocs is an innovative and rapidly expanding AI platform that revolutionizes the way insurance companies evaluate claims. With approximately $20 million USD in funding, over 100 team members worldwide, and more than 90 clients across North America and Australia, we are experiencing remarkable growth, doubling our revenue year after year.Founded by industry experts who have firsthand experience with the claims process, Wisedocs merges extensive domain expertise with cutting-edge AI, trained on over 100 million documents. Our platform simplifies complex medical records into clear, structured insights, supported by expert human oversight.Join our mission-driven team dedicated to developing intelligent products that simplify complexity, expedite decision-making, and create a significant impact when it matters most.Role OverviewWe are on the lookout for a Senior Machine Learning Engineer to spearhead the scaling and innovation of machine learning initiatives across the organization. In this pivotal role, you will enhance our inference and training pipelines to accommodate a higher volume of customers while refining extraction and summarization techniques across various modalities. You will foster a customer-centric approach and collaborate with fellow senior engineers to seamlessly integrate the ML system into the broader Wisedocs platform.Our Current ML EcosystemWe have three primary types of ML systems operational in production: an entity classification system, a custom reports generator, and a series of summarization models. Our entity classification has been functioning for four years and currently processes data asynchronously using a combination of models. Discover more about our initiatives at our tech blog.Recent Projects by Our ML Team:Reconstructing our inference pipeline to achieve 100x scalingDeveloping consistent parsing methods for 50,000-page PDFsDeploying our pipeline within an isolated government client environmentYour ResponsibilitiesDesigning and implementing machine learning models to analyze and interpret large sets of medical and insurance documentsCreating robust, scalable APIs using PythonCollaborating with technical stakeholders and leaders to contribute to system design and implementationEnsuring the reliability and scalability of ML systems while enforcing best practices in data engineering and model lifecycle managementWorking closely with our expert-in-the-loop teams to develop industry-leading evaluationsAdditional responsibilities will evolve as projects progress and change

Are you passionate about harnessing the power of machine learning to drive innovation in the mining industry? Stratum-AI is seeking a proactive and skilled Machine Learning Operations Engineer to become a vital part of our Infrastructure Team. In this role, you will play a key role in developing and maintaining the platform that trains, evaluates, and deploys our AI models, ensuring we deliver impactful solutions to our mining clients.Your expertise in Python and machine learning workflows will be instrumental as you collaborate with our talented team of engineers. Together, you will focus on creating a robust infrastructure and advanced tools that elevate our services.This is a fully remote position, allowing you to work from anywhere in Canada.

Join Stratum AI as a Forward Deployed Machine Learning Engineer and be part of our Technical Services team focused on tackling complex real-world challenges.In this role, you will work extensively with custom architectures using PyTorch, applying your expert knowledge of complex Convolutional Neural Networks, Graph Neural Networks, and Transformers.We prefer candidates based in Canada for this remote-first position.Technical Services Team ResponsibilitiesConduct foundational research to design and implement advanced AI resource modeling techniques applicable to various mining operations.Refine existing architectures to train resource models tailored for specific mines.Effectively communicate model quality, metrics, performance, and methodologies to non-ML technical stakeholders.Identify opportunities for enhancing mining operations and garner client support for new modeling parameters.Monitor deployed model performance over time and innovate on ways to improve existing models.Role ResponsibilitiesCustomize Stratum’s deep learning models for specific mining contexts.Develop and sustain high-quality machine learning code using Python.Explore innovative approaches to enhance resource and metallurgical models for specific mines.Allocate 60% of your time to applied ML for individual mines and 40% to foundational ML across multiple mines.Participate in a minimum of 2 mine visits annually to engage directly with clients.Develop into a senior engineer capable of identifying additional applications of our technology with existing clients.Navigate and thrive amidst complex datasets and evolving client needs, turning ambiguity into structured, actionable plans.Role RequirementsMinimum of 2 years of experience in machine learning or related fields.Proficient in Python and PyTorch with a strong foundation in deep learning principles.Experience with Convolutional Neural Networks, Graph Neural Networks, and Transformers is essential.Excellent communication skills, particularly in translating technical concepts to non-technical audiences.Strong analytical and problem-solving abilities, especially in ambiguous situations.

c-serv is forming an AI Red Team to improve the security of enterprise AI products. As an Adversarial Machine Learning Engineer, the focus will be on identifying vulnerabilities in large language model (LLM) systems and testing their defenses before they reach enterprise clients. This hands-on position addresses practical security challenges in real-world AI deployments. Main responsibilities Perform adversarial assessments targeting LLMs and other AI systems Simulate real-world attack scenarios, including: Prompt injection Jailbreaking and bypassing model guardrails Data exfiltration Model inversion and evasion Manipulation of retrieval-augmented generation (RAG) pipelines Develop scripts and tools to automate attack scenarios Evaluate model behavior and performance under adversarial conditions Identify weaknesses in technical components, such as: APIs Embedding pipelines Vector databases Fine-tuned model deployments Collaborate with engineering teams to verify fixes and improvements Document findings clearly and thoroughly Location This position is based in Calgary, Alberta, Canada. Impact The work in this role directly supports the reliability and security of AI systems before they are deployed at scale for enterprise use.

Join Our Innovative TeamSanctuary AI is at the forefront of developing dexterity-driven Physical AI for versatile robots. We are on the lookout for talented Machine Learning Engineers to become part of our dynamic team of engineers, researchers, and scientists. Together, we are committed to overcoming significant challenges in robotic perception, dexterous manipulation, planning, and reasoning.In this role, you will concentrate on creating robust systems to train and implement machine learning policies in robotic platforms. You will collaborate closely with researchers to introduce and execute cutting-edge ML techniques in production environments. Utilizing our state-of-the-art in-house robotic systems, you will design, test, and enhance software that connects advanced methodologies to practical outcomes. This role presents a unique opportunity to contribute to both the engineering foundations and the applied ML capabilities that propel our robots into the future.Note: Your role may require occasional travel (typically one to two weeks at a time, several times a year) to work closely with partners and teams on essential projects.

“Transform every logistics journey into a remarkable experience”Company Overview:Established in 2014, Quincus is a pioneering B2B SaaS platform specializing in supply chain operations, with its headquarters in Singapore. Our mission is to tackle the pressing challenges of global supply chains through innovative technology. By leveraging AI and machine learning, we have revolutionized the logistics landscape, providing our clients with unparalleled transparency and efficiency in their supply chain operations.Founded by two visionary entrepreneurs with over a decade of tech experience, Quincus is led by Chief Product Officer Katherina-Olivia Lacey, who champions a tech revolution while promoting women's empowerment within the supply chain sector. CEO Jonathan E. Savoir, recognized in Forbes' 30 Under 30 Asia List in 2020, also contributes to several startup boards, driving innovation forward.Role Overview:Quincus Research is at the forefront of developing the next generation of intelligent systems for our suite of products. We are seeking a highly motivated and skilled Machine Learning Engineer to join our dynamic team. You will play a pivotal role in designing and deploying deep learning and reinforcement learning algorithms at scale. Your expertise will be essential in creating scalable systems for model serving, optimizing inference performance, and managing production workflows.Key Responsibilities:- Design and implement scalable systems for deploying deep learning and reinforcement learning models.- Optimize the inference performance of models through advanced techniques like quantization, pruning, and distillation.- Leverage GPU computing to enhance model training and inference efficiency.- Develop and manage production workflows for the training and deployment of machine learning models.- Collaborate cross-functionally with data scientists and software engineers to create effective machine learning systems.- Monitor and enhance the performance of machine learning models in production.- Stay abreast of the latest advancements in deep learning and reinforcement learning methodologies.

Join bree as a Machine Learning Engineer, where you will be at the forefront of cutting-edge technology, developing algorithms and models that drive innovation. Collaborate with a dynamic team to enhance machine learning frameworks and contribute to impactful projects that transform data into actionable insights.

About Boson AI: At Boson AI, we are at the forefront of innovative AI solutions, shaping the future of enterprise AI. Our dedication to advanced AI research, especially in the realms of large language models and agentic systems, empowers us to address intricate real-world challenges for businesses and generate substantial value. Our vibrant and collaborative team of researchers and engineers is committed to pushing the limits of possibility, ensuring that we deliver high-quality, reliable products that integrate seamlessly into enterprise workflows and establish new benchmarks in the industry.About the Role: We are looking for a talented, detail-oriented, and driven Machine Learning Engineer to join our enterprise team. In this crucial position, you will spearhead the development and deployment of innovative AI solutions. This role entails integrating sophisticated language, voice, and vision models, mastering fine-tuning methodologies, constructing advanced workflows and platforms, and pioneering novel agentic strategies. You will engage with challenging problems that require a profound understanding of model behavior, precise implementation, and an unwavering dedication to quality and reliability in enterprise settings. A thrilling aspect of this role is your contribution to the architecture and implementation of intelligent systems where AI agents autonomously execute intricate tasks, interfacing with various data sources and tools, as we collectively strive to build truly integrated and powerful AI capabilities for our clients.

Join AuditBoard as a Senior Machine Learning Engineer I specializing in AI Governance, where you will play a pivotal role in shaping the future of AI technologies. Collaborate with cross-functional teams to develop and implement AI governance frameworks that align with ethical standards and industry regulations. Your expertise will help ensure that our AI systems are transparent, accountable, and trustworthy.

Role overview c-serv is seeking a Senior Machine Learning Engineer with expertise in Artificial Intelligence, Machine Learning, and Big Data. This position is fully remote and open to candidates residing in Canada. The role centers on applying technical depth to projects that shape the direction of technology within the company. What you will do Use advanced algorithms and data-driven methods to solve practical challenges on real-world projects. Collaborate with a skilled team to build and refine AI solutions. Offer technical insight that helps guide the development and improvement of key projects. Collaboration Work alongside professionals who value practical innovation and measurable outcomes. The team emphasizes open communication and collective problem-solving to achieve strong results.

Klue helps businesses transform scattered competitive data into clear, actionable insights. The Vancouver team is expanding and seeking a Senior Software Engineer with a focus on AI agent development. Role overview This position centers on designing and operating large language model (LLM)-powered agents at scale. Responsibilities span multi-agent orchestration, sub-agent design, and building evaluation frameworks to ensure outputs are both reliable and measurable. The work covers the full stack, including optimizing inference costs, improving retrieval and query performance, and creating feedback loops for ongoing system improvement. In addition to technical execution, this engineer will help shape the product roadmap by offering technical guidance and collaborating closely with product leadership. The role involves guiding projects from early architecture through experimentation and into production, always with an eye on production readiness and measurable results. What you will do Develop and deploy backend systems for agentic workflows. Design retrieval pipelines, orchestration layers, and agent architectures that process large volumes of competitive data, such as news, press releases, website updates, Slack messages, emails, reviews, and CRM data, into actionable intelligence for clients. Enhance LLM-powered workflows end-to-end. Work on prompt design, retrieval strategies, caching, and latency optimization to make agent responses fast, accurate, and reliable in production. Lead evaluations of agent systems at scale. Build and manage evaluation frameworks (automated, offline, and human-in-the-loop) to assess relevance, quality, latency, and overall task success. Define excellence metrics and set up infrastructure for ongoing measurement. Design and implement human-in-the-loop systems. Collaborate with product and design teams to propose and prototype feedback mechanisms, review workflows, and correction loops that help keep AI agents accurate and trustworthy over time. Location This role is based in Vancouver, British Columbia. Learn more about Klue at klue.com.

toloka-ai seeks a Freelance Machine Learning Developer for a contract position on its remote team. This role centers on building and improving AI systems for ongoing projects. Key responsibilities Collaborate with a distributed team to develop and enhance machine learning models Apply technical skills to projects that explore new AI methods Support the company’s machine learning work through hands-on development Location This position is fully remote and available to candidates residing in Manitoba, Canada.

Affinity integrates billions of data points from extensive datasets to craft a precise and powerful depiction of the global professional relationship graph. Our users gain essential insights and visibility to cultivate and leverage opportunities within their teams' networks. The position is part of the AI Platform team, responsible for the AI services that drive Affinity's premier relationship intelligence platform. Our work involves extracting and retrieving information from vast amounts of structured and unstructured data to provide actionable insights to our clients. As a Senior Machine Learning Engineer, you'll collaborate closely with data engineers, software engineers, and product managers to shape the future of the leading CRM platform in private capital. Your role will involve designing and building AI systems that efficiently uncover insights from dynamic business interaction data—an exciting and unique opportunity within the sector. This position focuses on applied machine learning with a significant emphasis on engineering rather than research. You will be instrumental in enhancing our ML Engineering capabilities, specifically in information retrieval and ultimately in recommendation systems. Key Responsibilities: Own the full ML lifecycle: Guide projects from ideation to production, encompassing feature engineering, model selection, deployment, and model observability and evaluation. Translate business needs into ML solutions: Gather product requirements and convert them into robust ML system design specifications. Build recommendation and ranking systems: Architect and implement ranking and recommendation infrastructure from the ground up, initially leveraging integrated off-the-shelf models and evolving to tailored solutions over time. Solve complex problems: Tackle diverse challenges in information extraction, storage, and retrieval for both structured and unstructured data. Collaborate cross-functionally: Work alongside cross-functional teams (product, infrastructure, data engineering, and software engineering) to develop robust, high-scale systems that underpin our data processing and ML operations.

Join Mistral as a Forward Deployed Machine Learning Engineer in Montreal, where you will play a pivotal role in applying cutting-edge AI technologies to real-world challenges. This position is ideal for innovative engineers passionate about leveraging machine learning to develop impactful solutions.

Later is the leading platform in influencer marketing, empowering brands to craft unforgettable campaigns with confidence. By leveraging genuine creator relationships, reliable intelligence, and expert support, Later eliminates uncertainty from one of marketing's most visible investments.Our AI-driven platform, backed by over a decade of proprietary data—including billions of social interactions, impressions, and more than $2.4 billion in verified influencer-generated purchases—enables teams to predict campaign success before launch.By merging valuable insights with expert guidance, Later takes the guesswork out of influencer marketing, allowing brands to select the ideal creators, execute thoroughly managed campaigns, and achieve significant growth in awareness, engagement, and revenue. Trusted by major enterprise brands such as Nike, Wayfair, Unilever, and Southwest Airlines, Later harmonizes creativity with performance to ensure campaigns not only look impressive but also yield tangible results. Discover more at later.com.About this Position:We are seeking a Machine Learning Infrastructure Engineer to join our expanding Data & Platform team. In this pivotal role, you will establish the framework that drives our AI and machine learning capabilities across Later's product suite. As our inaugural dedicated ML Infrastructure Engineer, you will oversee the systems that facilitate model experimentation, training, deployment, and large-scale monitoring.This position is essential for accelerating our data science endeavors and fostering future AI innovations. You will design and maintain reliable, secure, and scalable ML infrastructure that empowers data scientists and engineers to deploy impactful models confidently. If you are passionate about creating robust ML systems in a dynamic environment and are eager to set the standard for ML Ops at Later, this is your chance.

About this OpportunityJoin a global leader in networking that is transforming how businesses manage their networks. Our AI Core group is at the forefront, developing pioneering platforms across various domains such as Generative AI, AI Agents, RAG, Knowledge Bases, Data Mining, Anomaly Detection, and fine-tuning large language models. Here, innovation is not just welcomed; it is a core expectation.The RoleAs a pivotal AI ML Engineer, you will take on a leadership role in shaping our machine learning strategy. You'll be responsible for creating intelligent, high-performance multi-agent systems that can perceive, learn, and act in real-time.Key ResponsibilitiesDefine and lead the technical vision for machine learning solutions across our product portfolio.Manage the complete software development lifecycle, overseeing everything from design and code reviews to deployment and operational management.Architect robust, scalable microservices, including both synchronous and asynchronous web services.Develop real-time inference pipelines for complex models leveraging tools like Triton, TensorRT, and mixed-precision computing.Mentor fellow engineers, establish technical direction, and cultivate a strong team culture.Promote engineering excellence, system resilience, and continuous improvement in operations.

About Datatonic Datatonic stands as Google Cloud's top partner in AI, specializing in machine learning, data engineering, and analytics. The team helps clients across industries use advanced technology on Google Cloud Platform to modernize operations and uncover valuable insights. Role Overview The Senior Machine Learning Engineer position is a hands-on technical role based in Canada. This engineer writes production-quality Python code and prototypes solutions to complex problems. The role involves leading projects, collaborating closely with clients, and delivering reliable machine learning systems that address real business needs. What You Will Do Develop and maintain machine learning models using Python Apply strong engineering practices to both production systems and prototypes Lead project delivery and help scope new engagements Work directly with clients to understand challenges and deliver tailored solutions Build and maintain trusted client relationships What We Look For Solid foundation in machine learning and data science Experience selecting tools and methods for different ML applications Proficiency in optimizing and deploying ML models Strong communication and consulting skills Ability to deliver innovative AI and Cloud solutions for clients