Algorithm Engineer Jobs

NK Securities Research is a leading financial firm that leverages cutting-edge technology and sophisticated algorithms to trade the financial markets. Founded in 2011, we have gained invaluable experience in the field of High-Frequency Trading (HFT) across different asset classes. About the Role: We are looking for a Data Engineer to join our team at NK Securities. Data is at the core of everything we do, and this role will own how we source, store, validate, and understand it. You'll build reliable pipelines that bring data in from external sources, make sure it's clean and trustworthy, and dig into it to surface insights and issues before they become problems. You'll work closely with our trading, research, and tech teams. This is a high-ownership role for someone who cares about getting the details right and wants to grow into a key part of our data infrastructure. What You'll Do: Build and maintain pipelines to ingest data from multiple external sources, designed to be scalable and source-agnostic Design and implement data quality checks so that issues are caught early and automatically Handle data cleaning, missing values, and inconsistencies so downstream users can rely on the data Perform statistical analysis to identify anomalies, trends, and irregularities, and share clear reports with the team Maintain and manage databases, including backups, storage, and overall data health Develop a deep understanding of the datasets we use and serve as the go-to person for data-related questions Coordinate with internal teams and external providers to resolve data issues What We're Looking For: Strong programming skills in Python Good understanding of SQL and working with databases Familiarity with working with APIs and handling different data formats Solid foundation in statistics and data analysis Strong attention to detail and a habit of questioning data that doesn't look right Ownership mindset: you take responsibility for data being correct and available on time Ca

NK Securities Research is a leading financial firm that leverages cutting-edge technology and sophisticated algorithms to trade the financial markets. Founded in 2011, we have gained invaluable experience in the field of High-Frequency Trading (HFT) across different asset classes. Role Overview We’re looking for engineers who can take AI work beyond experiments and make it hold up in production. You’ll work closely with quant researchers and infra engineers to build AI systems that actually get used improving research speed and internal tooling without slowing down the core stack. We value engineers who think about trade-offs, test what they build, and care about how things run in production. What You’ll Build Production AI Ship models that meet defined latency and reliability expectation Add monitoring, rollback, and guardrails before anything goes live Optimise inference across CPU/GPU environments when it matters Integration into Real Systems Plug AI into data-heavy workflows without hurting performance Work within existing low-latency architecture instead of fighting it Profile and remove bottlenecks rather than guessing AI for Engineers & Researchers Build tools that genuinely speed up research and development Improve code understanding, review workflows, and internal knowledge retrieval Keep systems auditable and predictable LLM & Retrieval Systems Implement structured RAG and embedding pipelines with validation in place Create safe integration layers between models and internal systems Performance & Standards Track latency, drift, and stability — not just accuracy Build observability into everything you ship Help raise the bar for how AI is engineered here What We’re Looking For Strong Python fundamentals Clear thinking around system design and performance trade-offs Experience deploying AI systems in production (1–5 years is typical) Familiarity with transformers, embeddings, or LLM deployment Nice to have: Exposure to C++ / Rust / Go E

The Prediction & Behavior ML team is responsible for developing machine learning (ML) algorithms that learn and predict behaviors from data, applying them both on-vehicle to influence driving behavior and off-vehicle to provide ML capabilities to simulation and validation. Given the tight integration of behavior forecasting and motion planning, our team collaborates closely with the Planner team to advance overall vehicle behavior. We also work closely with our Perception, Simulation, and Systems Engineering teams to accelerate our ability to validate our driving performance. As a Learned Trajectory Machine Learning Engineer you will be responsible for developing deep learned models that produce trajectories for our vehicles to drive. Given the tight integration of behavior prediction and motion planning, you will closely collaborate with the Planner and Perception teams in the advancement of our overall vehicle behavior. In this role, you will: You will develop new deep learning models that use imitation learning and reinforcement learning to generate driving plans for our autonomous vehicle. You will also work on techniques to estimate the quality of those driving plans along the dimensions of safety, progress, comfort etc. You will leverage our large-scale machine learning infrastructure to discover new solutions and push the boundaries of the field You will develop metrics and tools to analyze errors and understand improvements of our systems You will collaborate with engineers on Perception, Planning, and Simulation to solve the overall Autonomous Driving problem in complex urban environments Qualifications BS, MS, or PhD degree in computer science or related field Experience with training and deploying transformer-based model architectures and reinforcement learning Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelines Fluency in C++

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. With a billion rides per year and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Rider, Marketplace, Growth, and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building a next-generation platform for low-cost, ultra-immersive transportation to improve people's lives warrants modern ML utilizing peta-byte scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. If you are a critical thinker with experience in machine learning workflows and LLMs, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you. We are seeking a Senior Machine Learning Engineer to join the Rider Applied AI team and lead the design, development, and deployment of state-of-the-art machine learning and artificial intelligence systems. This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation. You will collaborate across teams to shape the future of ride-sharing by leveraging AI, Machine learning and Data science. Responsibilities: Model Development & Research: Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions. System Design: Architect scalable, reliable ML pipelines that integrate seamlessly with existing backend systems. Innovation & Applied Research: Stay ahead of the curve by exploring emerging algorithms, technologies (such as LLMs and LLM-based applications), and frameworks — critically eva

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. With a billion rides per year and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Rider, Marketplace, Growth, and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building a next-generation platform for low-cost, ultra-immersive transportation to improve people's lives warrants modern ML utilizing peta-byte scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. If you are a critical thinker with experience in machine learning workflows and LLMs, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you. We are seeking a Senior Machine Learning Engineer to join the Rider Applied AI team and lead the design, development, and deployment of state-of-the-art machine learning and artificial intelligence systems. This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation. You will collaborate across teams to shape the future of ride-sharing by leveraging AI, Machine learning and Data science. Responsibilities: Model Development & Research: Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions. System Design: Architect scalable, reliable ML pipelines that integrate seamlessly with existing backend systems. Innovation & Applied Research: Stay ahead of the curve by exploring emerging algorithms, technologies (such as LLMs and LLM-based applications), and frameworks — critically eva

About Stitch Fix, Inc. Stitch Fix (NASDAQ: SFIX) Stitch Fix is redefining retail by combining human creativity with advanced data science and Generative AI. As we build the future of personalized shopping, we’re equally committed to building yours. We believe in investing in our team as much as our technology. Join us to be a trendsetter in the industry and help us redefine what’s possible for our clients, while we help you reach your full potential. About the Role The Client Experience Product Algorithms team is responsible for the machine learning, AI, experimentation, and product analytics capabilities that power personalized experiences for Stitch Fix clients and stylists. Partnering across Product, Engineering, Design, Styling, Marketing, Merchandising, Finance, Enterprise Analytics, Data Platform, and DSN, the team translates data and algorithms into measurable business impact. As Director, Product Algorithms, you will lead the strategy, execution, and people behind our Growth, Styling, and Fix & Freestyle Algorithms portfolios. You'll define how AI, machine learning, experimentation, and analytics shape the future of personalized shopping while building the operating discipline, technical excellence, and cross-functional alignment needed to deliver scalable business results. Responsibilities Lead the Product Algorithms portfolio across Growth, Styling, and Fix & Freestyle, setting strategy and driving measurable outcomes across acquisition, engagement, retention, styling quality, Fix, Freestyle, outfitting, and related commerce experiences. Define the vision and roadmap for applying data science, machine learning, AI, experimentation, and product analytics to improve client experiences, stylist effectiveness, and business performance. Drive innovation by identifying, evaluating, and scaling modern AI, machine learning, personalization, and experimentation techniques that create meaningful impact while balancing technical feasibility, exec

Join the MongoDB Networking & Observability team and help build the core of a distributed database! Our team focuses on creating and enhancing components which facilitate communication between distributed processes and make these processes, and their communication, easily observable. Networking Observability’s responsibilities include improving MongoDB networking, improving the efficiency of resource utilization, and building low-overhead observability features. Our team includes engineers located in New York City and fully remote engineers. We operate close to the bottom of the stack, and have a lot of influence over the availability, performance, and robustness of our open source database. Recently, we’ve improved connection handling, explored new networking architectures, and integrated OpenTelemetry to make issues easier to diagnose and connect MongoDB to modern observability tools. We are planning to further improve our networking’s stack performance, availability and scalability as well as further enhance our observability stack using open observability frameworks. Are you excited to help the MongoDB engineering team build a better database? We are! Join us today, and we can build a faster, more reliable, exceptionally observable, database system together. This role will be based remotely in Canada. Candidate Profile 3+ years of experience building distributed systems Passionate about delivering and deploying a product with cross-team stakeholders Solid computer science fundamentals, with strong competencies in data structures, algorithms, and software design/architecture Hands-on experience with building production-level code. Experience in C++ is required Interest in furthering their knowledge of networking, observability and how computer architecture and internals impact the availability of SaaS Solid verbal and written communication skills and highly motivated to collaborate with colleagues Position Expectations Understand and improve the current funct

Join the MongoDB Networking & Observability team and help build the core of a distributed database! Our team focuses on creating and enhancing components which facilitate communication between distributed processes and make these processes, and their communication, easily observable. Networking Observability’s responsibilities include improving MongoDB networking, improving the efficiency of resource utilization, and building low-overhead observability features. Our team includes engineers located in New York City and fully remote engineers. We operate close to the bottom of the stack, and have a lot of influence over the availability, performance, and robustness of our open source database. Recently, we’ve improved connection handling, explored new networking architectures, and integrated OpenTelemetry to make issues easier to diagnose and connect MongoDB to modern observability tools. We are planning to further improve our networking’s stack performance, availability and scalability as well as further enhance our observability stack using open observability frameworks. Are you excited to help the MongoDB engineering team build a better database? We are! Join us today, and we can build a faster, more reliable, exceptionally observable, database system together. This role can be based out of our New York City office or remotely within the United States and Canada. Candidate Profile 3+ years of experience building distributed systems Passionate about delivering and deploying a product with cross-team stakeholders Solid computer science fundamentals, with strong competencies in data structures, algorithms, and software design/architecture Hands-on experience with building production-level code. Experience in C++ is required Interest in furthering their knowledge of networking, observability and how computer architecture and internals impact the availability of SaaS Solid verbal and written communication skills and highly motivated to collaborate with colleagues Po

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are looking for a Localisation Engineer who can join our efforts in continuing to lead the industry in global localization and product translation in Tokyo, Japan. Responsibilities: Innovate localization strategy and lead complex technical projects across their entire lifecycle to continuously optimize processes. Design, build, and maintain a full-stack AI translation platform, including scalable web applications, backend services, and data pipelines. Integrate LLMs into core workflows to drive process automation, enhance content reuse, and support intelligent quality assurance. Establish comprehensive QA frameworks and provide ongoing technical support to ensure the robustness, reliability, and observability of localization pipelines. Manage vendor relationships, overseeing budget planning and ensuring high translation quality standards. Be excellent and think big in building the solution-based approach to offer the best localization at Snowflake. Required Qualifications: Minimum of a Bachelor's degree in Computer Science or related technical field or equivalent practical experience. Strong fundamental computer science skills. Knowledge of algorithms and data structures. 5+ years of experience in software development working with one or more of the following languages:

About Stitch Fix, Inc. Stitch Fix (NASDAQ: SFIX) Stitch Fix is redefining retail by combining human creativity with advanced data science and Generative AI. As we build the future of personalized shopping, we’re equally committed to building yours. We believe in investing in our team as much as our technology. Join us to be a trendsetter in the industry and help us redefine what’s possible for our clients, while we help you reach your full potential. About the Role The Client Experience Product Algorithms team is responsible for the machine learning, AI, experimentation, and product analytics capabilities that power personalized experiences for Stitch Fix clients and stylists. Partnering across Product, Engineering, Design, Styling, Marketing, Merchandising, Finance, Enterprise Analytics, Data Platform, and DSN, the team translates data and algorithms into measurable business impact. As Director, Product Algorithms, you will lead the strategy, execution, and people behind our Growth, Styling, and Fix & Freestyle Algorithms portfolios. You'll define how AI, machine learning, experimentation, and analytics shape the future of personalized shopping while building the operating discipline, technical excellence, and cross-functional alignment needed to deliver scalable business results. Responsibilities Lead the Product Algorithms portfolio across Growth, Styling, and Fix & Freestyle, setting strategy and driving measurable outcomes across acquisition, engagement, retention, styling quality, Fix, Freestyle, outfitting, and related commerce experiences. Define the vision and roadmap for applying data science, machine learning, AI, experimentation, and product analytics to improve client experiences, stylist effectiveness, and business performance. Drive innovation by identifying, evaluating, and scaling modern AI, machine learning, personalization, and experimentation techniques that create meaningful impact while balancing technical feasibility, exec

About the Opportunity Enabling millions of distributed energy devices to deliver reliable and predictable grid services to the electricity industry requires state-of-the-art forecasting, control systems, optimization algorithms, and data science. As such, EnergyHub seeks to hire a Senior Forecasting and Optimization Engineer to join EnergyHub’s Data Science and Power Systems Intelligence team. As a Senior Forecasting and Optimization Engineer you will work closely with some of the brightest minds in the electricity industry to solve some of the most difficult problems in distributed energy. The algorithms and data systems that you contribute to will be key to enabling a carbon-free distributed energy future. Main Responsibilities: What you’ll do Develop and improve accurate and robust energy forecasting models Develop and improve control and optimization algorithms Design, write, test, and deploy production-grade code for mission-critical forecasting and optimization products and related algorithms Build and use tools and processes to monitor and assess the quality of operational forecasting and optimization models Translate data from one of the largest distributed energy datasets in the electricity industry into actionable insights for electric utilities and other energy industry stakeholders Provide guidance to other engineers and scientists regarding machine learning, forecasting and optimization methods Present results clearly to internal and external stakeholders Collaborate closely with stakeholders inside and outside of EnergyHub including Data Engineering, Client Success, Marketing, Sales, Product, and Market Development teams Other duties as assigned Required Skills and Experience: What you need Passion for enabling a carbon-free, distributed energy future At least five years of experience in machine learning, statistical analysis, data visualization, control systems engineering, and/or mathematical optimization Experience developing data pipelines using la

The Prediction & Behavior ML team is responsible for developing machine learning (ML) algorithms that learn and predict behaviors from data, applying them both on-vehicle to influence driving behavior and off-vehicle to provide ML capabilities to simulation and validation. Given the tight integration of behavior forecasting and motion planning, our team collaborates closely with the Planner team to advance overall vehicle behavior. We also work closely with our Perception, Simulation, and Systems Engineering teams to accelerate our ability to validate our driving performance. As a Learned Trajectory Machine Learning Engineer you will be responsible for developing deep learned models that produce trajectories for our vehicles to drive. Given the tight integration of behavior prediction and motion planning, you will closely collaborate with the Planner and Perception teams in the advancement of our overall vehicle behavior. In this role, you will: You will develop new deep learning models that use imitation learning and reinforcement learning to generate driving plans for our autonomous vehicle. You will also work on techniques to estimate the quality of those driving plans along the dimensions of safety, progress, comfort etc. You will leverage our large-scale machine learning infrastructure to discover new solutions and push the boundaries of the field You will develop metrics and tools to analyze errors and understand improvements of our systems You will collaborate with engineers on Perception, Planning, and Simulation to solve the overall Autonomous Driving problem in complex urban environments Qualifications BS, MS, or PhD degree in computer science or related field Experience with training and deploying transformer-based model architectures and reinforcement learning Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelines Fluency in Pyt

Required Skills: Core Java: Strong understanding of Java SE, including OOP concepts, data structures, and algorithms. Frameworks: Experience with popular Java frameworks such as Spring and Hibernate. Web Technologies: Knowledge of web technologies including JSP, Servlets, HTML, CSS, and JavaScript. Database Management: Proficiency in working with relational databases like MySQL, PostgreSQL, or Oracle, including SQL queries and optimization. Version Control: Experience with version control systems like Git, including branching, merging, and pull requests. Build Tools: Familiarity with build tools like Maven or Gradle. RESTful Services: Ability to design and consume RESTful web services and APIs. Testing: Experience with unit testing frameworks like JUnit or TestNG. Problem-Solving: Strong analytical and problem-solving skills with the ability to troubleshoot and resolve complex issues. Preferred Skills: Spring Boot: Experience with Spring Boot for creating microservices. ORM: Proficiency with Object-Relational Mapping (ORM) tools like Hibernate or JPA. Frontend Technologies: Basic knowledge of frontend frameworks like Angular, React, or Vue.js. Cloud Platforms: Experience with cloud platforms such as AWS, Azure, or Google Cloud. Continuous Integration/Deployment (CI/CD): Familiarity with CI/CD tools such as Jenkins or GitLab CI. Microservices Architecture: Understanding of microservices architecture and containerization with Docker. Qualifications: Education: Bachelor’s degree in Computer Science, Information Technology, or a related field. Experience: 2-4 years of professional experience in Java development. Personal Attributes: Team Player: Ability to work collaboratively in a team environment. Communication: Strong verbal and written communication skills. Attention to Detail: High attention to detail and a commitment to delivering high-quality software. Adaptability: Ability to adapt to new technologies and changing requirements.

We offer a hybrid work environment. Most US-based positions can also be performed remotely (any exceptions will be noted in the Minimum Qualifications below.) Our Mission: To actively connect people to their next great opportunity. Who We Are: ZipRecruiter is a leading online employment marketplace. Powered by AI-driven smart matching technology, the company actively connects millions of all-sized businesses and job seekers through innovative mobile, web, and email services, as well as through partnerships with the best job boards on the web. ZipRecruiter has the #1 rated job search app on iOS & Android. Summary: With data such as a billion+ historical job postings, tens of millions of active job seekers interacting with our system, and hundreds of billions of impression and click events, there are incredible opportunities to use your skills to build new data-driven features. Working at ZipRecruiter, you will be helping literally millions of people find their dream job. We’re working on problems like: given a training set of job postings, and known salaries, build a system that predicts salary for novel jobs.Of course, you know that while building models is fun, it's also just one step in the process; gathering training data, cleansing it, digging into it, extracting features from it, etc, is a huge part of the job Key Focuses: Design, develop, and maintain advanced machine learning models and algorithms to solve complex business problems Lead complex machine learning projects that solve business challenges and add value to the broader ZipRecruiter Business Design the overall architecture and infrastructure for machine learning systems, ensuring scalability, efficiency, and robustness Push the boundaries of what's possible in machine learning in your organization, finding new and innovative ways to use AI to drive business value Provide leadership and set tone for Machine Learning Engineers at ZipRecruiter leveraging industry best practices an

We offer a hybrid work environment. Most US-based positions can also be performed remotely (any exceptions will be noted in the Minimum Qualifications below.) Our Mission: To actively connect people to their next great opportunity. Who We Are: ZipRecruiter is a leading online employment marketplace. Powered by AI-driven smart matching technology, the company actively connects millions of all-sized businesses and job seekers through innovative mobile, web, and email services, as well as through partnerships with the best job boards on the web. ZipRecruiter has the #1 rated job search app on iOS & Android. Summary: With data such as a billion+ historical job postings, tens of millions of active job seekers interacting with our system, and hundreds of billions of impression and click events, there are incredible opportunities to use your skills to build new data-driven features. Working at ZipRecruiter, you will be helping literally millions of people find their dream job. We’re working on problems like: given a training set of job postings, and known salaries, build a system that predicts salary for novel jobs.Of course, you know that while building models is fun, it's also just one step in the process; gathering training data, cleansing it, digging into it, extracting features from it, etc, is a huge part of the job Key Focuses: Design, develop, and maintain advanced machine learning models and algorithms to solve complex business problems Lead complex machine learning projects that solve business challenges and add value to the broader ZipRecruiter Business Design the overall architecture and infrastructure for machine learning systems, ensuring scalability, efficiency, and robustness Push the boundaries of what's possible in machine learning in your organization, finding new and innovative ways to use AI to drive business value Provide leadership and set tone for Machine Learning Engineers at ZipRecruiter leveraging industry best practices an