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Experience Level
Entry Level
Qualifications
Bachelor's degree in Computer Science, Data Science, or related field. Strong understanding of machine learning algorithms and frameworks. Experience with data preprocessing and feature engineering. Proficiency in programming languages such as Python and R. Familiarity with cloud computing platforms is a plus.
About the job
Join Prolific as an AI Training - Machine Learning Specialist! This is a unique opportunity to work in a fully remote environment where you will contribute to the development and enhancement of machine learning models. You will collaborate closely with data scientists and engineers to ensure the quality and efficiency of AI training processes.
As a key member of our team, your responsibilities will include optimizing training datasets, experimenting with various algorithms, and fine-tuning models to achieve high-performance outcomes. Your insights and expertise will help shape the future of AI at Prolific.
About Prolific
Prolific is a forward-thinking company dedicated to advancing the field of artificial intelligence. We prioritize innovation, collaboration, and excellence in everything we do. Our team is composed of talented professionals who are passionate about leveraging technology to solve real-world problems. Join us in shaping the future of AI!
About the RoleWe are seeking a passionate Machine Learning Engineer to spearhead the enhancement of model inference performance at scale. In this role, you will bridge the gap between theoretical research and practical application by transforming cutting-edge models into efficient, scalable, and user-centric systems.This position is perfect for individuals w…
About Agero:At Agero, we are at the forefront of transforming the vehicle ownership experience. Our mission is to innovate and enhance this experience through a unique blend of passionate individuals and data-driven technology, which strengthens the bonds between our clients and their customers. As the leading B2B, white-label provider of digital driver assistance services, we are redefining the industry by turning manual processes into digital, transparent, and connected solutions. Our offerings include an industry-leading dispatch management platform powered by Swoop, comprehensive accident management services, expert consumer affairs, and connected vehicle capabilities, along with a growing marketplace of services, discounts, and support powered by a strong partner ecosystem. We are proud to cover over 150 million vehicles in collaboration with major automobile manufacturers, insurance carriers, and more. Managing one of the largest national networks of service providers, Agero handles approximately 12 million service events annually. Headquartered in Medford, Mass., with operations across North America, we are a proud member of The Cross Country Group. To learn more, visit https://www.agero.com/.Note: For our technical roles, we encourage an in-person start! You may need to travel to Medford for your initial onboarding. Don't worry about the logistics; once you’re hired, we take care of all travel arrangements and expenses.Role Description and Mission:As the Engineering Manager for Data Science and Machine Learning, you will play a pivotal leadership role overseeing a talented team of Data Scientists, ML Engineers, and Software Engineers. Your focus will be on architecting, building, and operating our next-generation Dispatch Optimization platform. This position requires profound expertise in Data Science, Machine Learning, constrained Optimization (Operations Research), and the development of scalable cloud-native services.You will lead scientific rigor and engineering excellence to convert model outputs into real-time, high-impact dispatch decisions that optimize cost efficiency and enhance service levels.
Join our dynamic team at Ekumen Labs as a Machine Learning Data Engineer. In this role, you will leverage your expertise in machine learning and data engineering to design and implement robust data pipelines that facilitate the deployment of machine learning models. Your contributions will be crucial in transforming raw data into valuable insights that drive business decisions and enhance the efficiency of our operations.
About Us: Blue Rose Research is dedicated to creating innovative data and AI tools that empower Democrats to secure electoral victories. Our multidisciplinary team merges engineering, data science, and strategic political insight to fuel decision-making for leading campaigns and progressive organizations. We analyze electoral trends, test advertising strategies, and leverage generative AI to enable campaigns to respond effectively to current events with impactful messaging. Our guidance has influenced the allocation of hundreds of millions in campaign spending. As a compact, mission-driven team, we prioritize rapid development, bold experimentation, and assist progressives in communicating effectively and achieving success, all while driven by a sense of curiosity and a commitment to utilizing technology for positive change. Machine Learning Lead (LLM & Applied AI) We are seeking a Machine Learning Lead to oversee a team of skilled data scientists developing ML-driven solutions that inform strategies for civic leaders and organizations. Reporting directly to the Director of Engineering, you will take charge of the team’s roadmap and technical vision. This role is hands-on, requiring collaboration with your team to construct infrastructure, train models, and deploy them into production. If you are eager to apply your technical skills in a meaningful context that promotes public welfare, this position offers the opportunity to create a significant impact. Key Responsibilities: Lead a team of senior data scientists dedicated to optimizing large language models, conducting innovative R&D, and developing production inference systems. Work in partnership with senior leadership to establish the team’s roadmap and align priorities with organizational objectives. Facilitate weekly meetings and stand-ups to ensure team progress and remove any obstacles to execution. Provide technical guidance across projects utilizing open-weight and proprietary LLMs along with other advanced ML methodologies. Oversee testing, optimization, and data integrity to guarantee the accuracy, reliability, and readiness of models for production. Encourage creative problem-solving and methodological rigor when custom solutions are necessary beyond standard ML techniques. Convert complex model outputs into actionable insights for stakeholders, ensuring that our technical efforts yield real-world benefits. About You: 1+ years of experience leading data science teams; 6+ years in machine learning or data engineering. Strong foundation in applied statistics, model selection, tuning, and performance evaluation. Proficient in Python, SQL, and contemporary ML frameworks.
About the PositionWe are on the lookout for a Machine Learning Engineer specialized in model distillation to assist us in developing compact, rapid, and efficient models while maintaining high-quality standards. This role will involve blending research with practical applications—transforming state-of-the-art methodologies into scalable systems.This is a proactive role offering significant ownership: you will design distillation pipelines, conduct extensive experiments, and deliver models utilized in production environments.Your ResponsibilitiesDesign and implement knowledge distillation pipelines (including teacher-student, self-distillation, multi-teacher approaches, and more).Convert large foundational models into more compact, efficient, and cost-effective models for inference.Execute and scrutinize large-scale training experiments to assess quality, latency, and cost trade-offs.Work closely with research teams to adapt innovative distillation concepts into production-ready code.Enhance training and inference efficiency (memory usage, throughput, and latency).Contribute to the development of internal tools, evaluation frameworks, and experiment tracking systems.(Optional) Engage in contributing to open-source models, tools, or research.Ideal Candidate ProfileRobust background in machine learning and deep learning.Hands-on experience with model distillation techniques (including LLMs or other neural networks).Strong grasp of training dynamics, loss functions, and optimization strategies.Proficiency in PyTorch (or JAX) along with contemporary ML tools.Comfortable conducting experiments across multi-GPU or distributed configurations.Ability to critically evaluate model quality versus performance trade-offs.Pragmatic outlook: you prioritize deployment over merely publishing research.Preferred QualificationsExperience in distilling large language models or sizable sequence models.Familiarity with inference optimization techniques (like quantization, pruning, kernels, etc.).Experience in evaluating language models.Contributions to open-source projects or research publications.Experience in early-stage product development.
About Agero:At Agero, we're redefining the vehicle ownership experience. Our mission is to enhance the relationship between clients and their customers through innovative people and data-driven technology. As a leading B2B provider of digital driver assistance services, we are transforming traditional processes into efficient, digital, and connected solutions. Our offerings include a state-of-the-art dispatch management platform powered by Swoop, comprehensive accident management services, and a growing ecosystem of consumer support. Partnering with top automobile manufacturers and insurance carriers, Agero oversees 150 million vehicle coverage points and responds to approximately 12 million service events annually. Headquartered in Medford, MA, and part of The Cross Country Group, we operate across North America. To learn more, visit https://www.agero.com/.Note: For our technical roles, we prefer to start in person! You may need to travel to Medford for onboarding, but we will manage all travel arrangements and expenses for you.Role Description and Mission:The Engineering Manager for Data Science and Machine Learning is a pivotal leadership position responsible for overseeing a talented team of Data Scientists, ML Engineers, and Software Engineers dedicated to architecting, building, and operating our next-generation Dispatch Optimization platform. This role requires extensive expertise in Data Science, Machine Learning, Operations Research, and scalable cloud-native service development.You will champion scientific rigor and engineering excellence to convert model outputs into real-time, impactful dispatch decisions that enhance cost efficiency and service quality.
Hello,We are excited to present a fantastic opportunity for a GenAI Engineer within the dynamic field of AI and Machine Learning. This role is fully remote, allowing you to work from anywhere, and is a perfect fit for someone with extensive experience in developing prototypes and proofs of concept.Position OverviewAs a GenAI Engineer, you will leverage your deep understanding of AI and machine learning principles to create innovative solutions. Your expertise in Python and familiarity with tools such as Hugging Face, Langchain, and OpenAI API will be essential in driving project success.Key Responsibilities:Develop prototypes, PoCs, and MVPs using advanced AI/ML methodologies.Utilize deep learning frameworks including TensorFlow, Keras, and PyTorch to implement solutions.Engage with cloud platforms such as Google Model Garden, Amazon Bedrock, and Nvidia Nim to enhance project outcomes.Work collaboratively in a fast-paced environment, bringing innovative solutions to complex problems.Ideal Candidate:The successful candidate will possess a strong foundation in AI and machine learning, coupled with a passion for problem-solving and a collaborative mindset.
About the RoleWe are seeking a talented AI Researcher specializing in training optimization to enhance the efficiency, stability, and scalability of large-scale model training. This role involves working at the intersection of research and systems, where you will innovate techniques to lower training costs, speed up convergence, and enhance model quality—all while validating your concepts through rigorous experiments and publications.This position is perfect for individuals who thrive on transforming research insights into actionable training improvements and have a proven track record (or strong aspiration) of publishing applied machine learning research.Key ResponsibilitiesDesign and assess training optimization techniques for large-scale models, including optimization algorithms, schedulers, normalization methods, and curriculum strategies.Enhance training efficiency and stability for extended runs and vast datasets.Research and implement advanced methods such as:Innovations in optimizers and schedulersMixed-precision, low-precision, and memory-efficient training solutionsGradient noise reduction, scaling laws, and convergence analysisTraining-time regularization and robustness techniquesConduct large-scale experiments, analyze the results, and convert findings into practical improvements.Author or co-author research papers, technical reports, or blog articles.Collaborate closely with infrastructure and inference teams to ensure that training decisions yield real-world performance benefits.QualificationsStrong foundation in machine learning research, particularly in training dynamics and optimization.Proficiency in training large neural networks (LLMs, multimodal models, or extensive sequence models).Experience with publications in reputable ML venues (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, COLM, arXiv) or equivalent high-quality open research.Solid understanding of:Optimization theory and its practical applicationsBackpropagation, gradient flow, and training stabilityDistributed and large-batch training processes
At plantingspace, we are pioneering an innovative AI system tailored for analysts and scientists, leveraging a revolutionary approach to reasoning and knowledge representation. Our technology surpasses traditional state-of-the-art LLMs by intricately combining algorithms in a symbolic manner, enabling groundbreaking features such as multi-step analysis, transparent reasoning paths, and uncertainty assessment. We envision our applications transforming research and analysis across various fields, including Finance, Strategy Consulting, Engineering, Material Sciences, and beyond.We seek passionate Bayesian Software Engineers equipped with a solid background in Bayesian statistics to contribute to the development of our advanced models and algorithms for statistical inference and machine learning. Your role will involve designing, implementing, and optimizing statistical procedures that can be applied to a diverse range of models, all of which will be integrated within our expansive software system.
Poolside is committed to building Artificial General Intelligence within this decade. The company emphasizes rapid innovation, applied research, and large-scale deployment. By increasing the scale and capability of its models, Poolside aims to create economic value while focusing on user and customer success. The broader vision is to make AI central to meaningful work and scientific progress. The team works remotely across Europe and North America, meeting in person for three days each month and gathering for longer offsites twice a year. Researchers and engineers collaborate closely, sharing responsibility for building high-quality systems. Strong engineering practices support fast development and amplify results. Role overview The Reinforcement Learning Engineer role focuses on advancing the reasoning and coding abilities of Large Language Models using reinforcement learning. This position combines research and hands-on engineering: designing new training algorithms, developing and scaling RL environments, and implementing solutions throughout Poolside’s technology stack. Substantial GPU resources are available to support these projects. Mission Expand the reasoning and coding capabilities of foundational models through reinforcement learning. Key responsibilities Design and run experiments to improve reasoning and code generation in large language models. Oversee projects from initial idea through to integration. Stay current with the latest research in the field and contribute to ongoing research efforts. This is a remote position open to candidates based in EMEA or on the East Coast of North America. View GDPR Policy
Join Prolific as an AI Training - Machine Learning Specialist! This is a unique opportunity to work in a fully remote environment where you will contribute to the development and enhancement of machine learning models. You will collaborate closely with data scientists and engineers to ensure the quality and efficiency of AI training processes.As a key member of our team, your responsibilities will include optimizing training datasets, experimenting with various algorithms, and fine-tuning models to achieve high-performance outcomes. Your insights and expertise will help shape the future of AI at Prolific.
Poolside is dedicated to advancing Artificial General Intelligence (AGI), with a focus on innovation and engineering that drives economic and scientific progress. The company brings together experts in research and software development, all working toward high-quality systems. As a remote-first team, Poolside’s staff are based across Europe and North America. Team members meet in person for three days each month, with longer offsite sessions twice a year. This structure supports collaboration among people with both research and engineering backgrounds. Role overview The Reinforcement Learning Infrastructure Engineer joins the reinforcement learning team to improve reasoning and coding capabilities in Large Language Models (LLMs). The role covers the full process: researching new algorithms, designing and scaling RL environments, and implementing solutions across the stack. Work is supported by access to thousands of GPUs. Core mission Build and scale infrastructure for reliable, efficient LLM training using advanced reinforcement learning methods. Key responsibilities Stay current on research and developments in LLMs, reinforcement learning, and code generation. Develop strategies for fine-tuning training and inference, ensuring integration throughout the development process. View GDPR Policy
Join Prolific as a Machine Learning Specialist focused on AI Training! We are seeking a talented individual to contribute to the development and implementation of AI models. This is a fully remote position offering the opportunity to work with cutting-edge technology in a dynamic environment.As a key member of our team, you will analyze data, improve algorithms, and ensure the high performance of machine learning systems. Your expertise will help us drive innovation and optimize processes.
*]:pointer-events-auto scroll-mt-[calc(var(--header-height)+min(200px,max(70px,20svh)))]"> *]:pointer-events-auto scroll-mt-[calc(var(--header-height)+min(200px,max(70px,20svh)))]" data-turn-id="788a8b78-cfcd-42e1-beb1-30da5949a95d" data-testid="conversation-turn-8" data-scroll-anchor="true" data-turn="assistant">Join us at Prolific as a Machine Learning Specialist focused on AI Training! In this fully remote role, you'll leverage your expertise in machine learning to develop and enhance AI models, contributing to innovative projects that impact our clients globally. Collaborate with a talented team, participate in cutting-edge research, and help us drive the future of AI technology.
About TrafileaTrafilea is an innovative and dynamic Tech E-commerce Group that manages various direct-to-consumer brands in the intimate apparel and beauty sectors. We leverage data-driven strategies to scale our businesses and also foster an online community that champions body positivity. As a rapidly expanding global entity, we are dedicated to delivering high-quality products and services that enhance customer experiences and promote sustainable growth.1. MissionThe Senior CRO Specialist is pivotal in overseeing conversion performance throughout the customer journey, collaborating strategically with Growth, Product, Acquisition, Creative, and Data teams. This position is not merely about execution; it focuses on identifying conversion challenges, formulating impactful hypotheses, prioritizing experiments based on business significance, and ensuring alignment for the CRO team and squads to implement the most effective tests at optimal times.The Senior CRO Specialist operates with a business-centric perspective, comprehending funnels, user behavior, creative influence, and acquisition dynamics—transforming insights into actionable experimentation roadmaps designed to enhance CVR, revenue per session, and profit per visitor on a large scale.2. Core AccountabilitiesA. CRO Strategy & Experimentation OwnershipManage the complete CRO process: from problem identification to hypothesis formulation, prioritization, alignment, execution, and analysis.Identify conversion inefficiencies across funnels (landing pages, PDPs, checkout, quizzes, pricing, messaging).Establish clear hypotheses based on data and qualitative insights, rather than assumptions.Prioritize tests according to anticipated business impact, not solely ease of implementation.B. Cross-Functional LeadershipServe as the CRO authority for Growth, Acquisition, Product, Creative, and Data teams.Collaborate closely with:Acquisition & Creative → aligning messaging and hooks with the on-site experience.Product & CRO execution team → translating hypotheses into actionable tests.Facilitate CRO discussions without being solely responsible for execution.This role does not directly build all components — it ensures that the right elements are constructed and tested.C. Testing System & Quality StandardsGuarantee testing precision: effective setups, accurate KPIs, appropriate segmentation, and trustworthy conclusions.Maintain a well-organized testing backlog (not just inflated volume).
Canonical, a trailblazer in open source software and operating systems, is redefining the tech landscape for enterprises globally. Our flagship platform, Ubuntu, plays a pivotal role in transformative initiatives across public cloud, data science, AI, engineering innovation, and IoT. We proudly serve top-tier public cloud providers and prominent industry leaders across various sectors. Embracing a model of global collaboration, our diverse team of over 1,200 professionals spans 75+ countries, with minimal in-office roles. We convene bi-annually in unique global locations to align our strategies and execute our vision.As a growing, founder-led, and profitable company, we are excited to welcome a MLOps Solutions Engineer to empower enterprises to harness the power of AI/ML through cutting-edge open source technologies on both public and private cloud infrastructures, including Linux and Kubernetes. Our team offers expert insights to tackle real-world challenges, facilitating the adoption of Ubuntu, Kubeflow, MLFlow, Feast, DVC, and other advanced analytics and machine learning technologies. We are committed to developing the premier open source data platform, integrating traditional SQL databases with contemporary NoSQL data solutions while transforming data into actionable insights and executable models.This role is ideal for MLOps engineers who thrive on engaging with customers and addressing their challenges during the presales cycle. As solutions architects, you will innovate customer-centric solutions through architecture design, presentations, and training. This is primarily an architectural role focused on developing ML frameworks for external clients, rather than software development.We seek candidates with a robust technical foundation who possess a business-oriented mindset and are motivated by commercial success. As part of our global Field Engineering team, you will collaborate closely with enterprise sales leaders, tackling some of the toughest challenges in contemporary data architecture. Whether it’s training LLMs across hybrid cloud infrastructures with GPU sharing or processing millions of real-time financial transactions, you will be at the forefront of solving complex problems daily.Location: Most of our team operates remotely. We are expanding our teams across EMEA, Americas, and APAC time zones, making this opportunity accessible to candidates from nearly any location.
GenAI/ML Engineer100% Remote PositionW2 Candidates OnlyWe are seeking a talented GenAI/ML Engineer to join our innovative team at hudsonmanpower. This fully remote role allows you to leverage your expertise in artificial intelligence and machine learning to create prototypes, proofs of concept (PoCs), and minimum viable products (MVPs).Key Responsibilities:Develop and prototype cutting-edge AI/ML solutions.Utilize your strong foundation in AI, deep learning, and machine learning principles.Leverage programming skills in Python, along with tools such as Hugging Face, Langchain, and OpenAI API.Work with deep learning frameworks including TensorFlow, Keras, and PyTorch.Engage with cloud platforms like Google Model Garden, Amazon Bedrock, and Nvidia Nim.Handle multi-modal data and intelligent agent-based tools.Qualifications:Self-motivated and passionate about solving complex problems using AI/GenAI.Collaborative mindset with a flair for innovation.
Key Responsibilities:Platform Development: Architect, implement, and uphold a robust and scalable AI platform to effectively integrate, train, and deploy machine learning models.Infrastructure Optimization: Oversee and enhance cloud infrastructure (e.g., AWS, GCP, Azure) to meet high-performance AI workload requirements while ensuring cost efficiency.Cross-Functional Integration: Work collaboratively with various teams to merge AI capabilities with blockchain systems, prioritizing data security and compliance with decentralization principles. Contribute to decentralized app (DApp) and smart contract development as necessary.Security & Documentation: Establish and enforce stringent data security and privacy protocols for the platform. Develop and sustain comprehensive technical documentation to facilitate knowledge sharing and support future scalability.Innovation: Keep abreast of the latest advancements in AI, blockchain, and cloud technologies to promote ongoing innovation.Required Qualifications:Bachelor's degree or higher in Computer Science or a related discipline.Demonstrated experience in developing and deploying large-scale AI/ML platforms.Strong expertise in Python and familiarity with AI/ML frameworks such as TensorFlow and PyTorch.Practical experience with leading cloud platforms (AWS, GCP, or Azure).Comprehensive understanding of distributed systems and cloud-native technologies.Exceptional problem-solving abilities along with strong attention to detail and communication skills.Preferred Qualifications (Bonus Points):Knowledge of blockchain technology and smart contract development (e.g., Solidity).Experience with blockchain security best practices.Familiarity with DevOps tools and CI/CD pipelines.A record of contributions to open-source projects.What We Offer:Purpose: Be part of an initiative aimed at making AI a public good.Growth: A self-directed environment where you can take initiative to shape your role and career.Compensation: Competitive remuneration package.
About Our Team: Join the expanding Financial Assistant team at Platacard, where we are dedicated to creating intelligent systems designed to empower users in managing their finances, grasping spending habits, and seamlessly interacting with financial products. Our team is integral to enhancing customer experience, engagement, and the overall value of our core offerings. Operating in a regulated environment, we prioritize accuracy, safety, and trust. Utilizing AWS, Go, Python, and cloud-based models, we remain adaptable, integrating both off-the-shelf tools and custom solutions. Our focus is on crafting systems that yield significant and valuable results for our organization. As a pivotal member of our cross-functional team, you will collaborate with backend, mobile, and LLM engineers to drive innovation.
Join our innovative team as a Research Scientist specializing in Engineering, where your expertise in machine learning and generative media will drive the development of cutting-edge products. You will leverage your extensive knowledge of the latest advancements in the field to identify gaps in the market and create solutions that address real customer challenges. This role may involve pioneering new training methods or architectures, as well as fine-tuning existing models with unique datasets. Your ability to assess the return on investment for various approaches will be crucial, as we prioritize research that leads to tangible product development.
