Freelance Machine Learning Developer

Please submit your resume in English and indicate your level of English proficiency.At Mindrift, innovation and opportunity converge. We harness the power of collective intelligence to ethically shape the future of artificial intelligence.About UsThe Mindrift platform serves as a bridge connecting specialists with AI projects from leading technology innovators. Our mission is to unlock the potential of Generative AI by leveraging real-world expertise from around the globe.Role OverviewGenerative AI models are evolving rapidly, and one of our key objectives is to enhance their ability to tackle specialized queries and develop advanced reasoning skills. As a Machine Learning Engineer on our platform, you will have the unique opportunity to collaborate on such innovative projects.While each project is distinct, typical responsibilities may include:Designing original computational STEM problems that replicate authentic scientific workflows.Developing problems that necessitate Python programming for resolution.Creating problems that are computationally intensive, unsolvable manually within practical timeframes (days/weeks).Formulating problems that require complex reasoning and creative problem-solving techniques.Validating solutions using Python with standard libraries (numpy, pandas, scipy, sklearn).Clearly documenting problem statements and providing verified correct answers.Getting StartedTo apply, simply respond to this post, qualify, and seize the opportunity to engage in projects that align with your skills, on your own timetable. By creating training prompts and refining model responses, you will contribute to shaping the future of AI, ensuring that technology serves everyone.

Toloka AI is hiring a Freelance Machine Learning Engineer for a remote contract role based in Wisconsin, United States. This position centers on building and improving machine learning models that directly support product development and help shape the user experience. Responsibilities Create and fine-tune machine learning models for practical, real-world use Use data science techniques to enhance product features Work with other team members to solve technical challenges Requirements Solid background in machine learning and data science Proven ability to tackle complex problems using technical approaches Comfortable working independently as well as collaborating with a team Remote Work This contract role is fully remote but requires residence in Wisconsin, United States.

Role overview This freelance position at Toloka AI centers on designing and building machine learning models to support ongoing projects. The role is remote and requires residency in Iowa, United States. Independence is important, but collaboration with other engineers and specialists is also a key part of the work. The focus is on delivering practical solutions to technical challenges. What you will do Develop and implement machine learning models for different projects Work remotely as part of a distributed team Collaborate with peers to address complex technical problems and enhance current systems Apply your expertise to help Toloka AI achieve project goals Location This role is fully remote, but applicants must be based in Iowa, United States.

Toloka AI is hiring a Freelance Machine Learning Developer for remote contract work based in Iowa, United States. This position centers on supporting AI initiatives that require machine learning and artificial intelligence techniques. Role overview This contract role involves contributing to projects that apply machine learning and AI methods. Expect to work on tasks that require analytical thinking and technical skill in these areas. Location This is a remote position open to candidates located in Iowa, United States.

Role overview toloka-ai seeks a Freelance Machine Learning Engineer to join ongoing projects centered on practical AI solutions. This position is remote and based in Virginia, United States. What you will do Collaborate with a team of specialists to design and build machine learning models Create AI-driven solutions that address real-world challenges Contribute expertise and work remotely with colleagues on active projects Location This is a remote role for candidates located in Virginia, United States.

About the RoleJoin bjakcareer as we develop an innovative AI system designed to seamlessly manage workflows across various conversations, tools, and timeframes.In this pivotal role, you will take ownership of critical machine learning systems currently in production. We seek engineers who are capable of independently navigating complex ML challenges, from conceptualization to deployment, while making informed trade-offs throughout the process.Key ResponsibilitiesDesign and implement essential ML systems that drive a proactive, long-term AI product.Manage the entire ML process: data preparation, model training, evaluation, inference, and iterative improvement.Transform research concepts into stable, operational systems within a production environment.Troubleshoot model failures and system challenges using actual production data.Rapidly iterate: deploy solutions, assess results, refine processes, and repeat.Collaborate closely with research, product, and engineering teams to achieve meaningful user outcomes.Guide and review the work of fellow ML engineers, providing mentorship through your expertise and technical insight.Operate within the constraints of real-world production, considering factors such as latency, cost, reliability, and safety.Technical RequirementsProficiency in Python.Experience with PyTorch or JAX.Familiarity with GPU-based training and inference systems.Ideal Candidate ExperienceDemonstrated experience building and deploying ML systems utilized by end-users.In-depth understanding of the behavior of modern ML models, including their potential issues in production settings.Ability to write robust, production-level code while thinking in terms of systems rather than scripts.Proven track record of taking ownership, working independently, and driving projects to completion.Quick learner with clear communication skills and a dedication to continuous improvement through iteration.Company CultureAt bjakcareer, we embrace a flat organizational structure, fostering a small, highly driven team focused on engineering and product excellence. Every team member is expected to be actively involved and contribute directly to our mission.Interview ProcessIf your qualifications align with our needs, we will reach out to arrange between three to four interviews.

toloka-ai seeks a Freelance Machine Learning Developer for remote contract work based in Wisconsin, United States. This position offers flexibility in work arrangements and focuses on building solutions for a range of projects. Responsibilities Design and implement machine learning models tailored to project needs. Refine and optimize algorithms to boost performance and accuracy. Collaborate with teams across different functions to ensure solutions meet client requirements. Location This role is remote, but candidates must be located in Wisconsin, United States.

About NationGraphAt NationGraph, we are revolutionizing the accessibility and usability of public sector data for businesses targeting municipalities, state agencies, educational institutions, and specialized districts. Our advanced data intelligence engine extracts actionable insights from millions of public sector sources, empowering organizations to make informed decisions. Established in 2024, our mission is to democratize information, ensuring that public data is genuinely accessible to everyone. Discover more at nationgraph.comOur TeamComprises seasoned entrepreneurs who have successfully built, scaled, and exited multiple companies.Developed robust software infrastructure capable of processing billions in transactions.Supported by top-tier venture capitalists and seasoned operating partners with a track record of investing in and nurturing iconic brands.Role OverviewDesign and implement end-to-end machine learning pipelines.Extract and mine data from various online sources through large-scale web crawling and scraping techniques to enhance our models and insights.Convert unstructured text data into structured knowledge using natural language processing (NLP), entity recognition, and bespoke models.Develop and refine text classification models to systematically organize intricate datasets.Enhance retrieval-augmented generation (RAG) systems utilized in our product offerings.Drive our data strategy by identifying and integrating new data sources.Tackle open-ended technical challenges, fostering a culture of learning and collaboration within the team.Primarily utilize Python and SQL for development.QualificationsA strong quantitative background in fields such as computer science, physics, mathematics, or engineering.Solid foundation in mathematics and statistics.A PhD in a quantitative discipline.Expertise in Python programming.Proactive ownership mentality with the ability to address complex technical challenges to create commercial value.A genuine enthusiasm for continuous learning, growth, and uncovering insights from complex datasets.Strong problem-solving, communication, and collaboration abilities in a dynamic work environment.

About UsAt Iterative, we develop cutting-edge open-source tools designed for machine learning, including DVC (with over 12,000 ⭐ on GitHub), as well as robust enterprise data infrastructure solutions. Our innovative team collaboration SaaS solution, Studio, is also a part of our offering. As a well-funded (Series A) remote-first team with over 50 employees, we are dedicated to addressing the complexities involved in managing datasets, ML infrastructure, the lifecycle of ML models, and other data-centric workflows.We place a high value on collaboration and communication, both within our internal teams and in our interactions with users. We are committed to being responsive to the needs of our open-source community as well as our enterprise clients.Explore More: Website Documentation : GitHub Blog ⏯ YouTube DiscordJob OpportunityIn this role, you will delve into two aspects of DVC: the core functionality which involves managing data, pipelines, and related tasks such as optimizing data indexing and transfer, along with the user workflow experience. You will collaborate closely with our technical product managers to refine the user workflow, leveraging your taste and experience with MLOps tools or organizing ML infrastructure for your team. For instance, you will lead the enhancement of our current entry point into the ecosystem, dvclive, among other exciting projects.

At Vectara, we are revolutionizing the deployment of Enterprise AI Agents and AI Assistants, emphasizing Accuracy, Security, and Explainability like never before. Our enterprise RAG Platform stands out by utilizing advanced models for retrieval, embedding, and reranking, alongside a meticulously optimized LLM trained for quality and cutting-edge Hallucination Mitigation techniques. Our innovative approach has garnered recognition in esteemed publications such as the New York Times and Visual Capitalist, solidifying our reputation as leaders in responsible, production-ready AI solutions. With a diverse clientele of over 100 enterprises, including prominent US military organizations, financial institutions, healthcare providers, and manufacturers, we are committed to delivering exceptional results.Our founding team comprises seasoned professionals from Google, specializing in neural information retrieval and distributed systems. We invite you to join us in our mission to empower the world to discover meaningful insights. At Vectara, our team is built on passion and expertise, featuring top talents from companies like Google, Cloudera, Splunk, MongoDB, and Elastic.

Position OverviewAt Redo, we possess a wealth of e-commerce data points from over 3,000 merchants, and we're excited to explore the vast potential it holds. As our pioneering Machine Learning Engineer, you will play a pivotal role in unlocking this value.This is an individual contributor (IC) role where you will engage in coding daily, deploying models to production, and making foundational infrastructure decisions. We seek a motivated candidate who thrives in dynamic environments and is passionate about building innovative solutions.About RedoRedo is a cutting-edge post-purchase commerce platform that seamlessly integrates returns, order management, marketing, checkout optimization, and customer support into a unified system for e-commerce brands. Our mission is to empower over 3,000 merchants by transforming their post-purchase operations into a significant revenue stream.As a Series A company with nearly 200 employees, we are profitable and experiencing rapid growth, headquartered in Draper, Utah.Your ResponsibilitiesWe have early-stage ML models that demonstrate great potential, but we need your expertise to fully realize their capabilities. You will take ownership of model development, from research to deployment, make decisions regarding infrastructure and tooling, and define the technical direction for data science at Redo.Some exciting challenges you’ll tackle include:Product Recommendations - Generate upsell suggestions based on millions of transactions, utilizing purchase and return histories, cart data, and browsing behaviors to present optimal offers at crucial moments.Checkout Intent Prediction - Anticipate mid-session purchase probabilities to initiate tailored promotions before potential drop-offs occur.Inventory Forecasting - Estimate restock schedules and quantities across a vast array of SKUs, factoring in trends and seasonal variations.Additionally, you will identify and develop new high-value ML applications across our platform.You will enhance our ML infrastructure (we currently operate on a basic Metaflow/Sagemaker framework that you can improve or overhaul), collaborate closely with product and data teams to uncover new opportunities, and lead the function as it expands.Ideal Candidate ProfileWe are looking for someone who has successfully deployed models to production, diagnosed performance issues, and managed the complete model lifecycle. We prioritize what you have accomplished over formal qualifications.Proficient in Python and contemporary ML frameworks (e.g., PyTorch, scikit-learn).Experience in constructing ML infrastructure (including training pipelines, deployment, and monitoring processes).Strong data engineering skills: developing pipelines, complex SQL queries, and resolving data quality challenges.Action-oriented mindset; you prefer to ship and iterate rather than engage in endless planning.Business-oriented perspective; you focus on revenue implications, not just model performance metrics.Ability to operate independently as the sole ML professional for the foreseeable future.This position may not be suitable for those seeking a well-established ML team where they can learn from seasoned engineers.

Join Avride, an innovative leader in autonomous mobility, as we develop cutting-edge self-driving vehicles and delivery robots. Our mission is to revolutionize transportation and logistics, with our Labeling Team playing a critical role in realizing this vision.The Labeling Backend Team is responsible for establishing the data infrastructure that drives our research and development efforts in labeling pipelines, data preparation workflows, and model training processes. The high-quality labeled data we produce is essential for advancing our core technologies and supports a variety of models that underpin our business.About the RoleWe are seeking a talented Research Engineer dedicated to enhancing the quality and representativeness of the datasets that fuel our self-driving systems. In this role, you will design algorithms and tools for auto-labeling, data mining, and dataset monitoring, leveraging your strong Python engineering skills alongside applied machine learning concepts. Your contributions will significantly improve data efficiency, reduce labeling costs, and elevate model performance.Key ResponsibilitiesCreate and implement algorithms that optimize annotation processes, including auto-labeling systems that minimize manual effort and maximize throughput.Develop data-mining and active-learning pipelines to identify the most valuable samples for training.Establish dataset-quality monitoring systems that detect noise, redundancy, and low-value data.Construct analytical platforms (databases, dashboards, reporting) to monitor dataset quality and coverage over time.Collaborate closely with ML and Perception teams to integrate research findings into production workflows.Investigate emerging methodologies (vision-language models, weak supervision, uncertainty estimation) to enhance dataset quality and automation.

About VoltaiAt Voltai, we are pioneering the future of artificial intelligence by developing world models and agents capable of learning, evaluating, planning, experimenting, and interacting with the physical world. Our initial focus is on understanding and creating advanced hardware, electronic systems, and semiconductors, utilizing AI to design and innovate beyond human cognitive boundaries.About Our TeamOur remarkable team is backed by esteemed Silicon Valley investors, Stanford University, and industry leaders including CEOs and Presidents of Google, AMD, Broadcom, and Marvell. We boast a diverse group of former Stanford professors, SAIL researchers, Olympiad medalists, CTOs of prominent tech firms, and high-ranking officials with experience in national security and foreign policy.What We Are Looking ForExceptional AI/ML engineering skills, ideally from top-tier programs in Computer Science, Electrical Engineering, Mathematics, or Physics.Demonstrated success in delivering AI/ML projects from initial concept through to production deployment.Hands-on experience in fine-tuning and deploying large language models (LLMs) within production environments.Experience working with multi-modal models that integrate text, image, or audio inputs.Bonus PointsExperience in competitive programming.Contributions to open-source projects.Recognition through awards or publications in leading journals and conferences.Ability to thrive in a dynamic, fast-paced startup environment.

Join Orchard as a Machine Learning Engineer and play a pivotal role in transforming data into actionable insights. In this dynamic position, you will leverage your expertise in machine learning algorithms and data analysis to develop innovative solutions that enhance our products and services.We are looking for a proactive team player who thrives in a fast-paced environment and possesses strong problem-solving skills. You will collaborate with cross-functional teams, engage with large datasets, and contribute to the design and implementation of machine learning models.

Please submit your resume in English and indicate your English proficiency level. Mindrift connects skilled professionals with project-based AI work for leading technology companies. Projects focus on testing, evaluating, and improving AI systems. This is a freelance, project-based position rather than a permanent staff role. Role overview This freelance Data Science Engineer position centers on designing and validating challenging data science problems for real-world business scenarios. Work is fully remote and project-based, with a focus on Python and SQL. What you will do Design data science problems that mirror analytical challenges in industries such as telecommunications, finance, government, e-commerce, and healthcare. Create tasks requiring Python programming, using libraries like Pandas, Numpy, Scipy, scikit-learn, Statsmodels, Matplotlib, and Seaborn. Ensure problems are computationally intensive, with solutions that may require days or weeks to process. Develop scenarios involving advanced data processing, statistical analysis, feature engineering, predictive modeling, and generating business insights. Write deterministic problems with reproducible results by using fixed random seeds or avoiding stochastic elements. Base challenges on real business cases, including customer analytics, risk assessment, fraud detection, forecasting, optimization, and efficiency improvements. Cover the full data science workflow: data ingestion, cleaning, exploratory analysis, modeling, validation, and deployment considerations. Incorporate big data scenarios that require scalable computation strategies. Validate all solutions in Python, using standard data science libraries and statistical techniques. Document each problem clearly within a realistic business context and provide accurate, verified answers. Requirements Minimum 5 years of hands-on data science experience with proven business results. Portfolio of completed projects or publications demonstrating real-world problem solving. Advanced Python skills for data science, including experience with pandas, numpy, scipy, scikit-learn, and statsmodels. Strong background in statistical analysis and machine learning, with deep understanding of algorithms and their practical use. Expertise in SQL and database operations for data analysis and manipulation. Familiarity with Generative AI tools and concepts (LLMs, Retrieval-Augmented Generation, prompt engineering, vector databases). Understanding of MLOps and model deployment workflows. Knowledge of modern frameworks such as TensorFlow, PyTorch, and LangChain. Excellent written English communication skills at C1 level or above. How to join Apply Complete qualifications Join a project Fulfill assigned tasks Receive compensation Location Remote , Iowa, United States

Mindrift brings together professionals from around the world to work on AI projects for major technology companies. The team’s focus is on advancing Generative AI by connecting specialists with real-world expertise. Role overview This part-time, remote contract is for a Freelance Python Data Scraping Engineer (AI Pilot) supporting the Tendem project. Candidates must be based in Iowa, United States. The work centers on managing and carrying out web data extraction tasks, collaborating closely with Tendem Agents, and applying critical thinking to ensure the accuracy and relevance of collected data. Quality assurance is a key part of the position. What you will do Manage end-to-end data extraction workflows for complex websites, delivering structured datasets with precision and reliability. Use internal tools such as Apify and OpenRouter, along with custom workflows, to collect, validate, and process data according to project needs. Adapt scraping methods for dynamic web sources, including handling JavaScript-rendered content and responding to changing site behaviors. Apply strict data quality standards, running validation checks and systematic verification before delivering results. Scale operations for large datasets using batching or parallelization, monitor for failures, and maintain stability when site structures change. Requirements Minimum 3 years of experience in data engineering, web scraping, automation, or a related field. Compensation Earn up to $32 per hour, based on expertise and contribution speed. Actual pay may vary depending on project scope and complexity, and may differ across projects on the Mindrift platform. How to apply Submit an application through this posting to be considered for projects that fit your technical background and availability. Work may involve coding, automation, or refining AI outputs, all contributing to AI advancement and practical use cases.

About the Internship BlackSky is seeking a Machine Learning Engineer Intern for the Herndon, VA office. This role supports the team’s work on real-time global intelligence by helping to develop and improve machine learning models used in data analysis. What You Will Do Work closely with engineers and data scientists to design, build, and refine machine learning models Contribute to projects that strengthen BlackSky’s data analysis capabilities Collaborate in a team environment focused on technical problem solving

Join our innovative team at mercor as a Machine Learning Engineer specializing in Anonymization. In this role, you will harness the power of artificial intelligence to develop cutting-edge algorithms and solutions that protect user privacy while maintaining data utility. You will work closely with data scientists and software engineers to create advanced systems that anonymize sensitive data efficiently and effectively.

Special Notice This is a full-time position at webAI in Austin, TX. Employment is not tied to project awards or external funding. Role Overview webAI seeks a Senior Machine Learning Engineer to strengthen its Public Sector work. The focus: building and refining production-ready AI systems designed for secure, distributed environments. This role centers on moving models from prototype to reliable, scalable deployment, supporting government cloud platforms and edge devices, even where connectivity is limited or absent. What You Will Do Design and implement agentic workflows for multi-step reasoning, tool use, and automated decision-making in production systems. Convert research AI models into scalable systems used in real-world applications. Develop adaptive machine learning solutions using LoRA, PEFT, and on-device inference. Work with frameworks like PyTorch, TensorFlow, and Hugging Face Transformers to create, fine-tune, and optimize models. Apply model optimization methods such as quantization, pruning, distillation, and hardware-specific acceleration. Build and manage Retrieval Augmented Generation (RAG) pipelines, including integration with vector databases for contextual retrieval. Collaborate with multi-modal AI systems across computer vision, audio, and natural language processing domains. Improve model performance for distributed and resource-constrained environments, ensuring systems remain dependable under different connectivity scenarios. Requirements Active US Security clearance. At least 4 years of experience in applied AI, machine learning engineering, or production AI systems. Strong proficiency with PyTorch, TensorFlow, or Hugging Face Transformers. Hands-on experience deploying AI models to cloud, edge, and mobile hardware. Expertise in model compression and optimization (quantization, pruning, distillation). Background in building RAG pipelines and integrating vector databases.