Responsible AI Data Scientist

At CapTech, our Machine Learning Engineers play a pivotal role in creating and executing data-centric solutions tailored for our clients. We specialize in the design and deployment of scalable machine learning systems within enterprise frameworks. Our collaborative culture fosters an environment where you can learn from fellow analysts, architects, and clients alike.Key Responsibilities:Collaborate with clients, data scientists, engineers, and cross-functional teams to devise comprehensive machine learning solutions that align with business objectives.Translate client requirements into data-driven processes and analytical models.Conduct analysis and transformation of extensive datasets across various enterprise-level platforms such as AWS, Azure, and GCP.Design, develop, and implement sophisticated analytical solutions using client data, including recommender systems and natural language processing.Optimize and scale machine learning systems to meet client specifications and enhance performance.Advance CapTech’s Machine Learning and Data Science initiatives through client presentations, proposal writing, participation in business development activities, and mentoring junior data scientists and engineers.

As a Lead Machine Learning and Data Science Engineer at CapTech, you will spearhead the design and implementation of innovative, data-driven solutions for our clients, focusing on the development and deployment of scalable machine learning systems within enterprise frameworks. Our collaborative environment fosters continuous learning and knowledge sharing with fellow analysts, architects, and clients.Key Responsibilities:Collaborate with clients, data scientists, engineers, and cross-functional teams to devise end-to-end machine learning solutions that address evolving business needs.Provide technical guidance and ensure alignment of technical solutions with client requirements.Translate client requirements into actionable data-driven processes and analytical models.Examine and transform extensive datasets hosted on leading enterprise data platforms such as AWS, Azure, and GCP.Develop and deploy cutting-edge analytical solutions leveraging client-specific data, including recommender systems and natural language processing.Optimize and productionize machine learning systems to meet client expectations for performance and scalability.Enhance CapTech’s Machine Learning and Data Science practices by delivering engaging presentations, crafting proposals, participating in business development initiatives, and mentoring junior data scientists and engineers.

Join our dynamic team at Arrive Logistics as a Senior Machine Learning Operations Engineer, where you will play a pivotal role in optimizing our machine learning processes and enhancing operational efficiency. You will be responsible for deploying machine learning models into production, monitoring their performance, and collaborating with data scientists to ensure seamless integration with our existing systems.Your expertise in cloud computing and machine learning frameworks will be crucial in driving innovation and improving our logistics solutions. If you're passionate about leveraging technology to solve real-world problems and thrive in a fast-paced environment, we want to hear from you!

Join Inspire11 as a Machine Learning Engineering ConsultantAt Inspire11, we pride ourselves on being a team of curious, intelligent, and resourceful individuals committed to delivering exceptional quality. We foster a collaborative environment that encourages innovation and accountability. Our success is tightly aligned with the success of our clients, as we partner to simplify complexities, solve sustainable challenges, and continuously elevate our thinking. Value creation is not just a concept for us; it is an integral part of our daily operations.If you are ready to make a transformative impact and thrive in a space that values bold ideas and unique perspectives, Inspire11 is the place for you.

Make a Meaningful ImpactAs an Applied Machine Learning Engineer at Strata, you will be at the forefront of innovation, collaborating with architects, data scientists, AI developers, platform engineers, and product teams to integrate cutting-edge AI and ML capabilities into our healthcare platform. Your contributions will be pivotal in driving advancements in generative AI and beyond, as you employ a diverse array of machine learning techniques to tackle complex healthcare challenges. By developing next-generation AI agents, algorithms, and computational engines, you will play a crucial role in enhancing Strata's market leadership, streamlining operational efficiency, and empowering healthcare providers to deliver top-notch care while ensuring financial sustainability.A Day in Your RoleTransform the latest research (e.g., arXiv papers) into practical, production-ready solutions using Python.Prototype and refine machine learning models, focusing on regression, causal inference, optimization, and vector embeddings.Work collaboratively with cross-functional teams to seamlessly embed ML and AI functionalities into our software platform.Teaming up with data scientists, you will design experiments and apply statistical methods to analyze real-world data.Optimize, test, and scale ML models to support essential healthcare analytics.Our Technology EcosystemOur core platform serves over half of the nation's leading healthcare providers, enabling them to harness financial, operational, and clinical data effectively. Our AI and ML technology stack encompasses:Programming Languages & Libraries: Python, PyTorch, NumPy, Pandas, Polars, PyMCInfrastructure: AWS, Snowflake, Docker, GitHubTechniques & Tools:Regression (both Bayesian and non-Bayesian)Vector embeddings, similarity analysis, clustering techniquesCore statistics and distributions for exploratory data analysis (EDA)Optimization strategies (multi-armed bandit, mixed integer programming)Causal inference and probabilistic modeling

Join Signifyd, a leader in eCommerce fraud protection, as a Senior Machine Learning Engineer I / II. In this role, you will leverage advanced machine learning techniques to enhance our fraud detection systems. You will work collaboratively with a team of talented engineers and data scientists to develop innovative solutions that protect businesses from fraud.

Join Turnitin, a pioneering leader in the global education sector, where we have spent over 20 years collaborating with educational institutions to uphold principles of honesty, consistency, and fairness in assessments across all subjects. Our innovative products and services are utilized by more than 16,000 academic institutions, publishers, and corporations.At Turnitin, our default working model is remote, reflecting our respect for diverse cultures and personal choices. Headquartered in Oakland, our global presence includes offices in Dallas, Pittsburgh, Newcastle (UK), Stockholm (Sweden), Cologne (Germany), and Amsterdam (Netherlands). We cherish diversity and are committed to creating a community where every employee has equal access to learning and career opportunities, fostering a unique approach to talent recruitment from various backgrounds.As a Senior Machine Learning Scientist, you will play a crucial role in our ambitious product roadmap, working within a global team of dedicated scientists and engineers. Together, we aim to deliver innovative, well-engineered Machine Learning systems that integrate seamlessly into a wide array of learning, teaching, and integrity products.Your contributions will impact educators and students worldwide, as our Machine Learning technologies reach hundreds of thousands of instructors and millions of learners. With billions of papers submitted to the Turnitin platform and hundreds of millions of assessments graded on Gradescope and ExamSoft, your work will be at the forefront of revolutionizing educational tools.Key Responsibilities:Collaborate with subject matter experts and product owners to identify research questions and actionable insights.Curate, generate, and annotate datasets while adhering to responsible data collection and model maintenance practices.Translate raw data into trainable datasets using efficient SQL queries and scripting, visualizing results as needed.Develop and optimize machine learning models, ensuring robustness and readiness for production environments.

Join our innovative team at Turnitin, where Machine Learning is pivotal to our ongoing success. We have an ambitious product roadmap, and you will be a part of a global team of inquisitive and dedicated scientists and engineers, all committed to delivering state-of-the-art, well-structured Machine Learning systems. Collaborate closely with product and engineering teams across Turnitin to seamlessly integrate Machine Learning into a diverse array of learning, teaching, and integrity products.With Machine Learning being utilized by countless instructors teaching millions of students globally, your contributions will have far-reaching impacts. Our platform has processed billions of submissions, and your work will enhance our AI Writing detection system, automate feedback on student writing, explore authorship, and transform assessment creation and grading processes, among other vital back-end functions.Key Responsibilities:You will be part of an applied science group focused on modern Deep Learning. As a Senior Machine Learning Scientist, you will possess a balanced skill set encompassing both the scientific and software engineering aspects of (Deep) Machine Learning. Your primary focus will be on developing novel and deployable ML models and solutions in scenarios where existing solutions may not suffice. A strong understanding of the mathematical foundations of machine learning and deep neural networks is crucial, enabling you to devise novel model architectures, loss functions, and training methods. Staying updated with the latest AI and Deep Learning research across various modalities is essential, as you will apply these insights to your work.Although we utilize established training platforms, you will also create custom training loops. Models must be deployable in our products, necessitating proficiency in production-level coding and software engineering. You may train large models (with hundreds of billions of parameters), requiring expertise in multi-GPU and node training and familiarity with the latest training and inferencing advancements. Models must excel in production, balancing accuracy and computational costs effectively. Your role will routinely involve dataset exploration, generation (including synthetic datasets), design, construction, and analysis, which may occupy a significant portion of your time. Given the scale of data (billions of samples), the ability to write parallel and efficient pipelines is essential. Additionally, you will engage in code and model maintenance, hardening models for production pipelines, developing demos, and presenting your findings.

84.51° applies advanced data science to retail, supporting The Kroger Co. and partners with insights, loyalty marketing, and retail media products. The company draws on first-party data from over 62 million U.S. households through the Kroger Plus program, aiming to create more personalized shopper experiences. This position requires working in the office five days a week to foster collaboration and team connection. Role overview The Lead Data Scientist, Relevancy Sciences, joins a team focused on building and refining the science behind search and recommendation systems for Kroger’s e-commerce platforms. The team’s work shapes digital experiences for millions of customers, aiming for relevant, personalized, and scalable interactions across Kroger’s digital channels. What you will do Technical leadership and influence: Lead projects in search and recommendation systems, shaping scientific strategy to improve content discovery, relevance, personalization, and decision support. Identify impactful opportunities, clarify technical trade-offs, and guide the team toward practical, scalable solutions. Rapidly prototype and validate new ideas to demonstrate measurable value. Develop innovative search and recommender systems: Design and implement machine learning solutions for the grocery retail sector. Drive systems that enhance product discovery and personalization throughout the customer journey. Provide leadership in next-generation personalization, including Generative AI and agent-based approaches. Location This position is based in Cincinnati, OH or Chicago, IL.

Role overview ServiceNow is hiring a Staff Machine Learning Engineer focused on VoIP Infrastructure in Chicago. This role centers on applying machine learning to strengthen and scale voice-over-IP services. The work aims to improve performance, reliability, and scalability across the VoIP platform. What you will do Design and implement machine learning models tailored to VoIP infrastructure needs Work with teams from different disciplines to integrate ML solutions into existing systems Drive technical improvements that support high-quality, dependable VoIP services

Join us at imc as we push the boundaries of technology by deploying machine learning directly onto custom hardware. This is an exceptional opportunity for you to build innovative solutions from the ground up, influence our technical research direction, and witness your contributions make a significant impact in one of the world's most demanding computing environments.At imc, we develop our own hardware, software, and infrastructure, which empowers you to tackle bottlenecks directly without waiting on vendors or dealing with restrictive abstraction layers. If you are eager to explore the limits of computational possibilities, we invite you to apply. We are looking for both researchers and seasoned engineers from diverse backgrounds. Prior trading experience is advantageous but not necessary.

About CoinflowCoinflow is an innovative payments company based in Chicago, transforming the way money is transacted globally. We empower merchants and marketplaces to accept various payment methods across over 170 countries, ensuring instant settlements, leveraging AI for fraud prevention, and providing blockchain-based proof of delivery.With backing from top investors like Pantera Capital, CMT Digital, Coinbase Ventures, Jump Capital, and Reciprocal Ventures, Coinflow has recently secured $25M in Series A funding, propelling our mission to revolutionize cross-border payments.Since our inception in 2024, we have experienced remarkable growth, achieving a 23x increase in revenue and reaching a multi-billion-dollar annual transaction volume run rate!Role Overview:We are looking for a passionate Machine Learning Engineer to join our team, responsible for developing the intelligence layer that drives our platform. As our first dedicated ML hire, you will have the unique opportunity to shape how data and machine learning practices are integrated throughout Coinflow. You will analyze extensive transaction and behavioral data, create models and analytical systems, establish success metrics, and incorporate intelligence directly into our products and internal tools.The ideal candidate thrives on curiosity, is eager to experiment, and is driven to build innovative solutions that are yet to exist.Key Responsibilities:Design and refine machine learning models and analytical systems that enhance platform decision-making and product intelligence.Establish foundational practices for data and machine learning across the organization.Define, manage, and evolve key performance metrics related to platform health, performance, and risk.Investigate transaction and behavioral data to identify patterns, signals, and valuable insights.Collaborate closely with Engineering, Product, and Operations teams to transform open-ended challenges into concrete systems.Develop methodologies for evaluating, enhancing, and ensuring the reliability of models and data systems over time.Create internal workflows and tools that support operational and product teams.Contribute to shaping Coinflow’s long-term data and machine learning strategy.

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 IMC as a Machine Learning Engineer, where you will be instrumental in developing and deploying advanced machine learning models that enhance our global trading operations. Collaborate with top-tier researchers, hardware specialists, and software engineers to create innovative solutions that leverage GPU acceleration, distributed computing, and cutting-edge open-source technologies. Your contributions will significantly impact our trading strategies by streamlining experimentation cycles, fostering a culture of continuous improvement and innovation. This is a rare opportunity to tackle challenges at the convergence of machine learning and trading, allowing you to leave a lasting mark on the future of IMC's technology and trading prowess.

Role Overview ServiceNow is hiring a Principal Machine Learning Engineer focused on VoIP Infrastructure in Chicago. This position centers on building and improving systems that support reliable, high-quality voice over IP services. What You Will Do Develop and refine machine learning models to enhance VoIP system performance and reliability Design algorithms that address challenges in voice communication technology Work closely with teams across disciplines to deliver robust solutions for communication infrastructure Collaboration This role involves regular collaboration with cross-functional groups to shape the future of ServiceNow's communication technology.

Role Overview DoorDash is hiring a Data Science Manager to lead a team of data scientists working on projects that use data to improve DoorDash’s services. This role involves managing team members, setting direction for analytical model development, and shaping strategies that influence decisions across the company. What You Will Do Oversee and mentor a team of data scientists Guide the development of analytical models and data-driven strategies Work with teams from different departments to spot opportunities for improvement Deliver insights that help DoorDash connect people with top local options Locations San Francisco, CA Sunnyvale, CA Seattle, WA New York, NY Chicago, IL Austin, TX

As a Principal Machine Learning Scientist at Turnitin, you will play a pivotal role in shaping the future of our innovative products by leveraging the power of Machine Learning. Our ambitious product roadmap offers exciting opportunities for you to collaborate with a global team of inquisitive and skilled scientists and engineers. Together, we are committed to integrating state-of-the-art Machine Learning systems into a comprehensive range of educational products that enhance learning, teaching, and academic integrity.Your work will impact hundreds of thousands of instructors and millions of students worldwide. With billions of papers submitted to the Turnitin platform and millions of assessments graded across Gradescope and Examsoft, your contributions will have a significant global reach. You'll be at the forefront of our AI Writing detection systems, providing automated feedback on student writing, and revolutionizing assessment creation and grading while playing a vital role in our backend processes.Key ResponsibilitiesDevelop and deploy novel ML models and solutions, particularly in areas where pre-existing solutions are not available.Utilize deep understanding of machine learning mathematics and deep neural networks to create innovative model architectures, loss functions, and training methodologies.Stay updated on the latest advancements in AI and Deep Learning and apply these insights to your projects.Write production-level code, ensuring models are ready for deployment across our products.Train large-scale models, utilizing multiple GPUs and nodes, while optimizing for computational efficiency.Conduct thorough dataset exploration, generation (including synthetic data), design, construction, and analysis.Prepare and deliver presentations on your work internally and contribute to publications in peer-reviewed venues.

Join ColdQuanta as a Quantum Software Engineer, where you will harness your expertise in quantum-inspired classical machine learning and quantum machine learning (QML). In this pivotal role, you will develop cutting-edge ML models and algorithms utilizing tensor networks and other structured representations to support applications in quantum computing and quantum sensing platforms.As part of our innovative Quantum Software division, you will collaborate closely with teams across quantum computing and sensing hardware and algorithms to create scalable learning architectures that function within hybrid classical–quantum workflows. The ideal candidate will possess robust foundations in machine learning and mathematical physics, complemented by hands-on experience in crafting novel model architectures for structured, high-dimensional data.This position offers a unique opportunity to influence next-generation ML techniques that bridge classical and quantum paradigms for real-world applications.

8451 seeks a Senior Data Scientist Consultant to support the Managed Agent Platform. This role is open in Cincinnati, OH or Chicago, IL. Key responsibilities Analyze large, complex data sets in collaboration with cross-functional teams. Build predictive models that advance the Managed Agent Platform. Translate analytical findings into insights to guide strategic decisions. Help improve existing solutions and contribute to new developments for the platform. Requirements Significant experience in data science, including both model development and data analysis. Strong communication skills for effective teamwork and knowledge sharing. Proven ability to convert complex data into clear, actionable recommendations.