Senior Machine Learning Scientist

Upwork Inc. connects businesses with skilled professionals in AI, machine learning, software development, sales, marketing, customer support, finance, and accounting. The company’s platforms, including the Upwork Marketplace and Lifted, help organizations of all sizes find and manage freelance, fractional, and payrolled talent for a range of contingent work needs. Upwork supports both large enterprises and entrepreneurs in sourcing talent and implementing AI-driven solutions. The company’s network covers more than 10,000 skills, enabling clients to scale and adapt their workforce for changing business demands. Since launch, Upwork has processed over $30 billion in transactions. The company’s mission centers on expanding opportunities at every stage of work. Learn more Visit the Upwork Marketplace: upwork.com Learn about Lifted: go-lifted.com Connect on LinkedIn, Facebook, Instagram, TikTok, and X Follow Lifted on LinkedIn

Join Bumble Inc. as a Lead Machine Learning Engineer and drive innovation in our cutting-edge technology team. In this pivotal role, you will lead the design and implementation of machine learning algorithms, enhancing user experiences across our platforms. Collaborate with cross-functional teams to translate complex data into actionable insights, while mentoring junior engineers to foster growth and excellence within the team.

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.

At Bumble, we strive to foster a world where every relationship is both healthy and equitable. As an integral member of our AI & Matching team, you will be at the forefront of revolutionizing how millions of individuals connect, cultivate friendships, and discover meaningful relationships. Reporting directly to our SVP of AI & Data, your contributions will be pivotal in enhancing intelligent systems that provide safe, personalized, and engaging user experiences across all our platforms. In this influential individual contributor role, your work will tangibly influence product strategies, user trust, and large-scale business outcomes. You will operate with a profound sense of ownership and curiosity, advocating for innovative machine learning methodologies while exemplifying Bumble's core values of Curiosity and Excellence. From reimagining recommendation systems to integrating responsible AI standards, your efforts will help us push boundaries while remaining respectful of our global community. AI is central to our product evolution and internal capabilities. In this position, you will not only develop and scale advanced machine learning models, but also influence how AI is thoughtfully and responsibly implemented throughout the organization.

Join our innovative team at Allen Control Systems as a Machine Learning Data Engineer. In this pivotal role, you will leverage your expertise in machine learning, data processing, and engineering to design and implement data pipelines and algorithms that enhance our data-driven initiatives. You will collaborate closely with data scientists and software engineers to deliver cutting-edge solutions that drive business insights and efficiencies.

About Striveworks Striveworks helps organizations use artificial intelligence to solve real-world problems, especially in national security. Founded by data scientists and engineers, the company focuses on making AI deployment and ongoing optimization simpler and more reliable. Striveworks partners with clients to build systems that adapt, scale, and perform well in unpredictable situations, supporting critical operations and informed decision-making. Role Overview: Senior Machine Learning Engineer The Senior Machine Learning Engineer will take on a key position, contributing to both customer projects and Striveworks’ core product suite. This role involves working with the Chariot AIOps platform to create solutions that bridge data, models, and operational needs. Collaboration is central: expect to work closely with data scientists, software engineers, and DevOps professionals to turn machine learning models into real operational tools. This position is open to candidates in Austin, Texas or those seeking a remote arrangement. A hybrid option is available for those near the Austin office. Main Responsibilities Work with customers, engineers, and stakeholders to define requirements that align with client needs and leverage the AI operations platform. Develop machine learning models and analytics for various types of data, including images, video, text, geospatial, time series, and structured datasets. Automate and manage complex data engineering and analytics workflows. Contribute to the design and implementation of core product features. Participate in mission-critical fieldwork as opportunities arise. Who Thrives Here This role suits engineers with a strong technical background who enjoy building customer-focused solutions and collaborating across disciplines. Effective communication, a focus on delivering repeatable value, and a drive to solve practical challenges are essential. Clearance Requirement An active Secret clearance is required for this position.

Innovate, Deploy, and Sustain AI Solutions for a Dynamic EnvironmentAt Striveworks, we empower organizations to leverage artificial intelligence to address pressing national security and business challenges. Serving as the pivotal hub connecting data, models, and impactful business results, we simplify the journey from deployment to continuous optimization.With Striveworks, companies are not merely implementing AI; they are developing robust systems that are trustworthy, versatile, and primed for growth in an unpredictable landscape. We understand that mission-critical operations demand models that not only excel in their deployed environments but also scale with increasing workloads and swiftly adapt as AI technologies evolve. Striveworks addresses these requirements, enhancing reliability and performance while reducing costs, thus fostering informed, data-driven decision-making in fast-paced settings.The OpportunityAs a Staff Machine Learning Engineer at Striveworks, you will be entrusted from day one to play a pivotal role and serve as a technical leader directly engaging with customers on key projects and the company’s strategic direction. Your mission-critical tasks will include designing AI-driven solutions, implementing them—from data preparation and ingestion through analysis to user delivery—and shaping future platform capabilities.You are an ideal candidate if you have a strong technical foundation and a desire to push your limits. Your enthusiasm for utilizing both software engineering and data science to tackle real-world issues is paramount. You should comfortably lead a team while directly executing vital components of the project and articulating the vision and results to customers.Your daily responsibilities will encompass:Collaborating with customers, engineers, and stakeholders to establish clear requirements that address customer challenges and exploit our AI operations platform's capabilities.Converting requirements into a technical approach, comprehensive design, scoping estimate, and execution strategy.Leading project teams to ensure timely delivery of project outcomes aligned with customer business objectives while making significant individual contributions throughout the process.Designing, orchestrating, and automating sophisticated data pipelines and algorithms within contemporary architectures (cloud, event-driven, microservices, etc.).Steering the creation of machine learning models and specialized analytics applied to image, video, text, geospatial, time series, and structured data.Identifying insights, opportunities, challenges, and feedback to enhance team practices and capture reusable functionality.

Avride develops autonomous vehicles and delivery robots across the United States, building and operating both autonomous cars and delivery robots with shared core technologies. The company focuses on advancing both fields together through integrated research and engineering. Internship overview The Machine Learning Engineer Internship in Austin, TX offers hands-on work with real driving data and exposure to advanced academic research. Interns join the Perception team, which interprets raw sensor data, including cameras, LiDAR, and microphones, to construct a detailed, real-time 3D view of the environment for autonomous vehicles. Each intern works directly with a senior mentor and contributes to projects that influence the safety and performance of Avride’s systems. The internship bridges theory and practice: interns help turn new concepts and system architectures into working prototypes, then assess their effectiveness in complex, safety-critical scenarios. What you will do Four distinct internships are available within the Perception team for Summer 2026. Projects focus on 3D perception and sensor fusion challenges in autonomous driving. Long-Tail 3D Entity Recognition via Pre-Trained 2D Models Lead efforts to address long-tail entity recognition, a persistent challenge in autonomous driving, by exploring how pre-trained, open-source 2D models can enhance 3D recognition tasks. Design and run simulation-based experiments to test whether models can identify rare or infrequent objects while maintaining precision. Work closely with a mentor to prototype and refine methods for integrating 2D model features into Avride’s perception stack. Present findings, including recall and precision trade-offs, and simulation methodologies, to Avride’s research and engineering teams at the conclusion of the internship. RGB-Only 3D Perception & RGB-LiDAR Fusion Take ownership of a targeted research project aimed at improving 3D perception by reviewing current literature on RGB-only approaches and developing hypotheses to advance sensor fusion techniques.

Join Our Innovative TeamAt avride, we are at the forefront of revolutionizing transportation through our cutting-edge autonomous vehicle technology. Our dedicated team is responsible for creating the essential software and data processing frameworks that enable motion planning and decision-making in self-driving cars. We thrive at the crossroads of machine learning, extensive data infrastructure, and real-time vehicle control, collaborating closely with engineering, analytics, and product teams to provide safe and intelligent driving solutions.Position OverviewWe are seeking a passionate and innovative Machine Learning Engineer to join our autonomous vehicle division. In this pivotal role, you will contribute to the development of intelligent systems capable of comprehending, predicting, and safely navigating the complexities of the real world. Your responsibilities will encompass designing and training advanced deep learning models that serve as the cognitive core of our vehicles, utilizing vast amounts of real-world driving data. If you have a keen interest in leveraging state-of-the-art ML techniques to tackle high-stakes robotics challenges, we encourage you to apply.Key ResponsibilitiesDevelop, train, and implement advanced machine learning models for behavioral prediction and motion planning.Create efficient data pipelines to process, cleanse, and annotate large-scale vehicle sensor and simulation datasets.Utilize deep learning architectures such as transformers to capture intricate temporal interactions among traffic participants.Define and manage metrics for model performance, establishing evaluation frameworks that align with on-road safety and efficacy.Collaborate with software engineers to integrate and optimize trained models for real-time inference on vehicle hardware.Keep abreast of the latest advancements in machine learning, imitation learning, and reinforcement learning, applying innovative methodologies to our systems.QualificationsExpertise in Python with practical experience in modern deep learning frameworks (e.g., PyTorch, TensorFlow, or JAX).Strong grasp of machine learning principles, including various neural network architectures, training techniques, and evaluation methods.Experience across the complete machine learning lifecycle, from data exploration and model prototyping to deployment and monitoring.Proficient in C++ for developing high-performance inference code for models.Preferred QualificationsDemonstrated success in ML competitions (e.g., Kaggle) or significant contributions to prominent open-source ML projects.Experience applying machine learning to real-world problems in robotics or autonomous systems.

Join Bumble Inc. as a Senior Machine Learning Engineer and contribute to our mission of creating meaningful connections. In this role, you will design, develop, and implement machine learning algorithms that enhance user experience and drive innovation. You will collaborate with cross-functional teams to deliver data-driven solutions and improve our platform's performance.

Join Avride as a Machine Learning Platform Engineer, where you will be at the forefront of developing cutting-edge machine learning solutions. In this pivotal role, you will collaborate with data scientists and software engineers to build robust ML infrastructure, driving innovation and efficiency.

Role Overview Bumble Inc. is hiring a Staff Machine Learning Engineer in Austin, Texas. This role focuses on building and refining machine learning algorithms that support Bumble’s AI-powered products. The work directly impacts user experience and engagement across the platform. What You Will Do Design and implement machine learning models for real-world product features Optimize algorithms to improve performance and user outcomes Work with teams across engineering, product, and data to identify new opportunities for applying machine learning Translate data insights into practical solutions that shape product direction Collaboration This position partners closely with colleagues from different functions, bringing together technical expertise and business perspective to drive innovation on the Bumble platform.

About the TeamAt Avride, we are pioneering the future of transportation through our groundbreaking autonomous vehicle and delivery robot technology. Following the successful launch of our robotaxi service in Dallas, we are on a mission to accelerate innovation and transform mobility as we know it.Our dedicated team is at the forefront of building self-driving solutions from scratch, with machine learning as the cornerstone of our development process, enabling safe and intelligent navigation. We create and deploy cutting-edge models to tackle the significant challenges in autonomous systems, utilizing advanced deep learning architectures like Convolutional Neural Networks (CNNs), Transformers, and Multimodal Large Language Models (MLLMs). Your contributions will be vital in enhancing the performance, safety, and reliability of Avride's autonomous vehicles and delivery robots.

Who is SonarSource?At SonarSource, we are dedicated to enhancing code quality and security while boosting developer productivity through innovative AI solutions. Our platform examines all code—whether it's authored by your internal team, generated by AI, or supplied by third parties—ensuring the creation of secure, reliable, and maintainable applications. With roots in the open source community, SonarSource supports over 30 programming languages, frameworks, and infrastructure technologies. Over 7 million developers and 400,000 organizations globally, including prominent names like the DoD, Microsoft, NASA, MasterCard, Siemens, and T-Mobile, trust our solutions.We pride ourselves on building exceptional products backed by a strong internal culture. Our team is deeply committed and passionate about our mission, our users, and each other. We uphold high standards, holding ourselves accountable for positivity, dedication, thoughtfulness, empathy, and daily passion.Our decision-making is deliberate and clear, yet we operate with a sense of urgency and agility.As a unified team, we strive for effectiveness and operational efficiency in achieving our goals.At SonarSource, CODE is not just an acronym — it embodies our operational ethos.Why You Should Join Us:We are a vibrant team of talented professionals determined to empower developers to create better software more efficiently. Our solutions continuously enhance code quality and security, alleviating developer burdens, allowing them to focus on their passions. We address root causes rather than just symptoms, ensuring high-quality output across all types of code.Our dynamic culture spans the globe with offices in the USA, Switzerland, the UK, Singapore, and Germany. We foster an environment where every team member feels proud of their work, energized by their colleagues, and excited to contribute to a mission that truly matters: supercharging developers.Your Impact:As a key technical architect, you will guide our strategic enterprise clients and partners in implementing and deploying our machine learning solutions. As one of the pioneering Forward Deployed ML Engineers, you will play a crucial role in shaping our ML offerings for organizations focused on quality, security, and operational excellence.

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.

Who We AreAt Arrive Logistics, we are a premier transportation and technology firm in North America, dedicated to substantial growth year after year. Our achievements reflect the strength of our exceptional team and the innovative solutions we are developing together. We prioritize delivering a meaningful work experience for our employees and have cultivated an award-winning culture that encourages personal and professional development within a fun, relaxed, and collaborative atmosphere. Now is the perfect time to join us, so read on to discover more and apply today!Who We SeekAs a Senior Machine Learning Operations Engineer at Arrive, you will play a pivotal role as a technical leader, responsible for defining, advancing, and executing our comprehensive machine learning platform strategy. This position involves driving and contributing to the quality and functionality of critical roadmap projects, which may include deploying models at scale and creating ML-powered services aimed at optimizing profitability.

About Us: At webAI, we are pioneering the first comprehensive private AI platform tailored for enterprises and governments, enabling them to harness AI capabilities directly on their data. Our unique approach to artificial intelligence emphasizes specialization, sovereignty, efficiency, and sustainability, addressing real-world challenges rather than simply increasing computational demands. Our innovative technology empowers the creation of robust AI systems using minimal data, defying the conventional belief that vast datasets are essential for unlocking AI's potential. Join us to be part of a rapidly expanding team that values a dynamic and growth-focused work environment, where your contributions can lead to meaningful advancements for society.About the Role: We are in search of a highly skilled Senior Staff Machine Learning Engineer specializing in Large Language Models (LLMs) and Mixture of Experts (MoEs). The ideal candidate will possess a solid history of developing and successfully deploying cutting-edge AI models.Responsibilities: Drive the advancement and refinement of Large Language Models and Mixture of Experts systems.Collaborate effectively with interdisciplinary teams to embed machine learning models into our platform.Engage in pioneering research within the machine learning domain, focusing on enhancing the performance and efficiency of LLMs.Keep updated with the latest trends and breakthroughs in AI and machine learning, applying insights to enhance our models and practices.Mentor junior engineers, fostering knowledge sharing and promoting best practices within the team.Qualifications: Ph.D. or advanced degree in Computer Science or a related discipline.Established track record of innovation and contributions to the field, evidenced by publications or substantial industry experience.A minimum of 6 years of hands-on experience in machine learning, with specialized knowledge in Large Language Models and Mixture of Experts.Proficient programming skills in Python along with experience using machine learning frameworks such as TensorFlow and/or PyTorch.Proven ability to lead complex projects and collaborate effectively in a team-oriented environment.

IMPORTANT: Please be aware, scammers may try to impersonate Zello by reaching out regarding job opportunities. We will never ask you for bank account information, checks, or other sensitive information as part of our hiring process. All correspondence will come from the zello.com email domain. If you’re unsure, please email recruiting@zello.com with questions.About ZelloZello is a premier voice-first communication platform that leverages our cutting-edge push-to-talk technology to enhance collaboration and productivity for desk-less workers. With over 175 million users globally, we proudly stand as the leading push-to-talk app worldwide, facilitating an astonishing 9 billion messages each month.We are deeply committed to our core values, which guide our mission daily. We take pride in supporting frontline workers, connecting individuals during crisis situations around the world, and honoring our commitment to first responders.And this is where you come in.Zello's Data & AI team has successfully launched customer-facing AI features (such as the Ella assistant, AI Insights, message summaries, and AI-driven search) and is currently developing the internal AI infrastructure that will enhance the efficiency and effectiveness of all teams within the company. We are seeking an engineering intern who can tackle real operational challenges—such as support triage bottlenecks, manual data workflows, and fragmented internal knowledge—and create functional AI-powered tools. This is a hands-on role focused on building rather than merely observing or researching.The RoleYou will report to the Head of Data & AI, collaborating with the AI engineering team to design and implement internal productivity tools powered by LLMs, embeddings, and automation. The ideal candidate is someone who has independently built projects utilizing LLMs—not just because it was assigned, but out of genuine curiosity and a desire to see it come to fruition. You will have significant autonomy, real users, and tangible impact from your very first week.After a Successful Internship, You Will Have:Delivered at least two internal AI tools that are essential to Zello teams on a weekly basis—be it an automated triage agent, a CRM enrichment pipeline, an LLM-driven Slack workflow, or something entirely new.Made substantial contributions to Zello's AI platform infrastructure—such as enhancements to embeddings pipelines, RAG systems, evaluation frameworks, or reusable components for future projects.Dramatically reduced manual effort in at least one operational workflow, providing clear before-and-after metrics to demonstrate your impact.Created comprehensive documentation that enables others to easily understand and build upon your work.

Company Overview avride builds autonomous vehicles and delivery robots, with machine learning at the core of every product. The team recently launched a robotaxi service in Dallas, and continues to design self-driving solutions from the ground up. Machine learning models, including CNNs, Transformers, and Multimodal Large Language Models, power both on-board and off-board systems, supporting safe, intelligent navigation and efficient operations. Role Overview: Senior / Staff Machine Learning Engineer avride is hiring experienced Machine Learning Engineers at Senior, Staff, and Principal levels in Austin, TX. The team welcomes both strong individual contributors and technical leaders ready to shape the future of autonomous mobility. This role focuses on solving complex challenges in autonomy, from developing deep learning models to managing large-scale datasets and deploying solutions in real-world systems. Senior-level engineers will also help set technical direction, mentor peers, and influence machine learning practices across the company. Main Responsibilities Model Development and Optimization: Design, implement, and improve deep learning models for tasks such as environmental perception and road user behavior prediction. Staff and Principal engineers will set the technical vision for model families and guide architectural choices across teams. Dataset Management: Oversee data collection, preprocessing, and augmentation to maintain high-quality datasets for training and evaluation. Senior engineers will define standards and tools that scale across the organization. Training Pipeline Enhancement: Build efficient workflows for training, validation, and testing. This includes distributed training, hyperparameter tuning, and automated monitoring. Staff and Principal engineers will own the long-term roadmap for training infrastructure. Model Deployment and Efficiency: Optimize inference performance, model compression, and deployment across a range of hardware platforms. Location This position is based in Austin, TX.