About the Role The Machine Learning team at Tubi drives the innovation behind personalized user experiences. With the largest inventory in the industry and hundreds of millions of viewers, we tackle problems in the space of recommendations, search, content understanding, and ads optimization that shape the future of streaming. We are seeking a VP / Director of Machine Learning Engineering to lead and build a high-performing team while staying close to the technical work. This is a hands-on leadership role: you will set the strategic direction for our recommendation, personalization, and ads optimization systems, including recommendation foundation modeling, and you will stay in the algorithms and the code, conducting deep dives into modeling components and guiding the hardest technical decisions yourself. You will tackle complex machine learning problems at scale and partner closely with cross-functional teams to ship solutions that measurably improve how hundreds of millions of viewers experience Tubi. What You’ll Do Lead, build, and grow a high-performing ML engineering team, fostering a culture of technical excellence, ownership, and rapid iteration. Define and drive the ML strategy and long-term technical roadmap for recommendation, personalization, and ads optimization, including recommendation foundation modeling, identifying opportunities for ML to shape Tubi’s broader product and business strategy. Stay hands-on: conduct deep dives into algorithmic components and systems, ensuring models are optimized for both performance and scalability across regions and product areas. Lead the design, development, and implementation of advanced recommendation systems and algorithms, contributing directly to the most challenging technical problems. Build and deploy robust, full-stack ML pipelines: data extraction, feature development, model training, testing, deployment, and serving. Continuously monitor, evaluate, and optimize the performance of deployed models, ensuring
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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 across different asset classes. With a focus on innovation, entrepreneurship, and collaboration, we aim to foster a dynamic work environment that reflects a startup culture. Role Overview As an FPGA Developer, you will design, implement, and rigorously test RTL (Register-Transfer Level) designs to power our high-frequency trading strategies. Your contributions will play a pivotal role in reducing system latency and enhancing performance, directly impacting trading outcomes. Key Responsibilities Design and Implementation: Develop high-performance RTL designs using VHDL or Verilog for FPGA-based systems. Optimize hardware implementations for ultra-low latency and high throughput. Testing and Debugging: Perform thorough functional and timing testing of RTL designs, ensuring adherence to specifications. Debug and resolve issues using FPGA debugging tools such as SignalTap, ChipScope, or ModelSim. Collaboration and Documentation: Work closely with hardware and software teams to ensure seamless integration of FPGA solutions with the Software Trading Stack. Maintain clear and comprehensive documentation of designs, test cases, results and benchmarks Qualifications Technical Skills: RTL Development: Strong fundamentals in digital logic design, Boolean algebra, FSMs and synchronous design. Proficiency in VHDL or Verilog/SystemVerilog, with a strong focus on efficient and optimized designs. FPGA Tools: Hands-on experience with industry-standard tools such as Xilinx Vivado. Testing and Verification: Expertise in writing testbenches and conducting simulation-based verification. Familiarity with static timing analysis and achieving timing closure. Familiar with CocoTB or any similar testing setup. Debugging: Proficiency in GHDL synthesis a
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 across different asset classes. Key Responsibilities: As a Software Developer - Platform, you will play a vital role in building and enhancing tools that empower our Quant, Infrastructure, Compliance, and Operations teams. In addition to web application development, you will be responsible for automating critical infrastructure processes, optimizing tasks, and delivering scalable solutions for our trading ecosystem. Application Development: Develop and maintain in-house software tailored for business and trading requirements. Enhance internal tools and applications to improve the user experience for different teams. Ensure robust and reliable trade monitoring systems through continuous innovation. Automation Development: Design and develop frameworks to automate infrastructure provisioning, configuration, and deployment using latest industry best practices Automate exchange-specific tasks such as connectivity management, order book monitoring, and trade execution workflows. Task Optimization: Identify and optimize repetitive tasks through scripting and configuration management. Ensure scalable and adaptable solutions to support multiple exchanges and regions. Infrastructure as Code (IaC): Use Ansible to codify infrastructure configurations, ensuring consistency and repeatability. Manage playbooks for server setups, network configurations, and middleware deployment. System Monitoring and Maintenance: Develop tools for system health checks, performance monitoring, and logging. Automate response mechanisms for critical alerts and incidents. Collaboration: Work closely with infrastructure, network, and trading teams to gather requirements and deliver robust solutions. Coordinate with exchange connectivity teams to ensure complianc
Hyliion is committed to creating innovative solutions that enable clean, flexible and affordable electricity production. The Company’s primary focus is to develop distributed power generators that can operate on various fuel sources to future-proof against an ever-changing energy economy. Job Purpose The Advanced Engineer, Power System Controls plays a key role in the design, development, and implementation of control software for Hyliion’s Karno Power Module. This position focuses on systems involving combustion, thermal management, pressure regulation, high-voltage, and power management. The engineer will be responsible for developing and validating control algorithms, tuning system parameters, and analyzing data to ensure performance meets engineering specifications. Additional responsibilities include preparing technical documentation, supporting root cause analysis, and ensuring timely, high-quality software delivery. The role requires cross-functional collaboration and occasional travel to support system testing and troubleshooting. Duties and Responsibilities Design, develop, and implement high-quality control software for Hyliion’s Karno Power Module, which includes combustion, thermal, pressure, high-voltage and power management systems. Define and conduct tests to verify software and tune control parameters to meet key performance indicators. Prepare reports and technical documentation related to system performance, control strategies, and compliance. Process and analyze data to verify software against engineering specifications, support root cause analysis and for optimizing performance. Ensure on time delivery with quality. Assist product team in defining customer requirements and generate corresponding engineering specifications. Qualifications Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Qualifications include: Education, Experience and Cert
Java Developer Roles and Responsibilities Write maintainable/scalable/efficient code. Work in a cross-functional team, collaborating with peers during the entire SDLC. Follow coding standards, unit-testing, code reviews etc. Follow release cycles and commitment to deadlines. Qualifications & Experience Experience level of 1 to 2 years of experience in very large scale applications. Fair understanding in problem solving skills, data structures and algorithms. Experience with distributed systems handling large amounts of data. Fair understanding in coding skills in Java/J2EE, Web technologies, RDBMS/messaging.
Roles and Responsibilities- ? Write maintainable/scalable/efficient code. ? Work in a cross-functional team, collaborating with peers during the entire SDLC. ? Follow coding standards, unit testing etc. ? Follow release cycles and commitment to deadlines. Qualifications & Experience ? 1+ years of experience in large scale applications. ? Problem solving skills, data structures and algorithms. ? Experience with distributed systems handling huge data. ? Coding skills in Java/J2EE. ? Good understanding of Web Technologies. ? Good understanding of any RDBMS and/or messaging.
Roles and Responsibilities Write maintainable/scalable/e?cient code. Work in a cross-functional team, collaborating with peers during the entire SDLC. Follow coding standards, unit-testing, code reviews etc. Follow release cycles and commitment to deadlines. Qualifications & Experience Experience level of 3 to 5 years of experience in very large scale applications. Fair understanding in problem solving skills, data structures and algorithms. Experience with distributed systems handling large amounts of data. Fair understanding in coding skills in Java/J2EE, Web technologies, RDBMS/messaging.
Roles and Responsibilities Write maintainable/scalable/code Work in a cross-functional team, collaborating with peers during the entire SDLC. Follow coding standards, unit-testing, code reviews etc. Follow release cycles and commitment to deadlines. Qualifications & Experience Experience level of 3 to 6 years of experience in very large scale applications. Fair understanding in problem solving skills, data structures and algorithms. Experience with distributed systems handling large amounts of data. Fair understanding in coding skills in Java/J2EE, Web technologies, RDBMS/messaging.
Roles and Responsibilities Write maintainable/scalable/e?cient code. Work in a cross-functional team, collaborating with peers during the entire SDLC. Follow coding standards, unit-testing, code reviews etc. Follow release cycles and commitment to deadlines. Qualifications & Experience Experience level of 3 to 5 years of experience in very large scale applications. Fair understanding in problem solving skills, data structures and algorithms. Experience with distributed systems handling large amounts of data. Fair understanding in coding skills in Java/J2EE, Web technologies, RDBMS/messaging.
Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: The Relevance and Personalization team at Airbnb is responsible for search and recommendation across the entire Airbnb digital platform. Be a leader in the team working on critical, impactful projects with focus on developing end-to-end ranking algorithms and ecosystems for optimizing multiple critical business objectives. The Difference You Will Make: We build cutting-edge AI technologies across the end-to-end search ranking product stack w.r.t. data pipelines, feature and model innovations, serving and experimentation efficiency, leveraging rich signals from various types of data (structured, sequential, image, text, etc) at Airbnb. We collaborate closely with teams across Airbnb to develop the ranking solutions and support a healthy marketplace for hosts and guests to further Airbnb’s mission of creating a world where people can Belong Anywhere. Some past publications from the team can be found here: https://sites.google.com/view/airbnb-relevance-publications/home A Typical Day: Work with large scale structured and unstructured data, build and continuously improve cutting edge Machine Learning models for Airbnb product, business and operational use cases. Work collaboratively with cross-functional partners including software engineers, product managers, operations and data scientists, identify opportunities for business impact, understand, refine, and prioritize requirements for machine learning models, drive engineering decisions, and quantify impact. Hands-on develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and
ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE The Model Performance organization at Baseten is looking to hire our first Technical Program Manager. This is a zero-to-one role in a team that is responsible for building the core algorithms and methods that power Baseten’s high performance inference stack. You won't inherit an existing program framework, you'll build one from the ground up: the planning structure, execution processes, metrics and the cross-functional alignment that a fast-growing organization needs. Your contributions will directly impact how fast our performance R&D gets productized. If you can drive turning a set of ambitious but loosely defined initiatives into a predictable, well-governed program, this role is for you. EXAMPLE INITIATIVES Take a look at these blog posts written by members of our Model Performance team: How to build a day-0 API for Kimi K3 How we built the new fastest API for GLM-5.2 Inference engineering for DeepSeek V4 Pro 0813 RESPONSIBILITIES Own execution across Model Performance's active project portfolio, freeing the team's technical leads to focus on technical direction rather than tracking. Design and stand up the planning structures, operating cadences, and status reporting mechanisms that best fits the team’s DNA. Coordinate model release and optimization programs end to end, including day-zero launches, sequencing the work across performance engineering, infra, and release stakeholders. Drive cross-team al
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. The Mapping team at Lyft is tasked with building a digital representation of the physical world - a map. We collect and serve the freshest and most accurate mapping data possible, along with algorithms, models, platform services, and map-based user experiences that power Lyft’s current and future transportation offerings. Mapping represents a huge opportunity for Lyft’s business, but also a big challenge. We build and scale systems that deal with large data storage, real-time data processing, machine / deep learning pipelines, routing and ETA models, driver and passenger location tracking, and more. We built beautiful and magical user experiences on top of all those services, and compete with companies that have been in the mapping business for decades. Our engineering team is growing rapidly, and we are looking for Engineering Managers to help us scale. Our engineers are smart, flexible, and love solving difficult challenges. They look to their managers for organizational transparency, career development, mentorship, and honest feedback. They move fast and ship code to production continuously, relying on their leadership to increase productivity by removing obstacles and keeping processes lean. Responsibilities: Manage a rapidly growing team of engineers developing user-facing Mapping experiences Mentor and guide the professional and technical development of your team members. Help develop their careers and assign them to projects tailored to their skill levels, personalities, work styles, and professional goals Build teams that are collaborative, inclusive, and respectful of each other Provide continuous feedback, address underperformance, and recognize the individual strengths and contributions of your team members Create plans for prioritizing technical and resourcing challenges in your organizat
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. The Mapping team at Lyft is tasked with building a digital representation of the physical world - a map. We collect and serve the freshest and most accurate mapping data possible, along with algorithms, models, platform services, and map-based user experiences that power Lyft’s current and future transportation offerings. Mapping represents a huge opportunity for Lyft’s business, but also a big challenge. We build and scale systems that deal with large data storage, real-time data processing, machine / deep learning pipelines, routing and ETA models, driver and passenger location tracking, and more. We built beautiful and magical user experiences on top of all those services, and compete with companies that have been in the mapping business for decades. Our engineering team is growing rapidly, and we are looking for Engineering Managers to help us scale. Our engineers are smart, flexible, and love solving difficult challenges. They look to their managers for organizational transparency, career development, mentorship, and honest feedback. They move fast and ship code to production continuously, relying on their leadership to increase productivity by removing obstacles and keeping processes lean. Responsibilities : Manage a rapidly growing team of engineers developing user-facing Mapping experiences Mentor and guide the professional and technical development of your team members. Help develop their careers and assign them to projects tailored to their skill levels, personalities, work styles, and professional goals Build teams that are collaborative, inclusive, and respectful of each other Provide continuous feedback, address underperformance, and recognize the individual strengths and contributions of your team members Create plans for prioritizing technical and resourcing challenges in y
Who we are About Stripe Stripe, LLC. is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. What you’ll do Responsibilities Design state-of-the-art ML models and large-scale ML systems for underwriting and portfolio management for Stripe Capital based on ML principles, domain knowledge, risk, regulatory and engineering constraints. Design systems to speed up the time from idea to deployment of new models. Experiment and iterate on ML models (using tools including PyTorch and TensorFlow) to achieve key business goals and drive efficiency. Develop pipelines and automated processes to train and evaluate models in offline and online environments. Integrate ML models into production systems and ensure their scalability and reliability. Collaborate with product and strategy partners to propose, prioritize, and implement new product features. Engage with the latest developments in ML/AI and take calculated risks in transforming innovative ML ideas into productionized solutions. Who you are Minimum requirements Must have a Bachelor's degree or foreign equivalent in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field, plus two (2) years of experience in Building and shipping ML systems in production. Must have two (2) years of experience in each of the following: ML algorithms and model architectures; Designing, training and evaluating machine learning models; Productionizing and deploying machine learning models at scale; Orchestrating data pipelines and leveraging large-s
About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Who You Are We're looking for innovative and passionate Machine Learning Engineers to join our team. You are someone who loves solving complex problems, enjoys the challenges of working with huge data sets, and has a knack for turning theoretical concepts into practical, scalable solutions. You are a strong team player but also thrive in autonomous environments where your ideas can make a significant impact. You love utilizing machine learning techniques to push the boundaries of what is possible within the realm of Natural Language Processing, Information Retrieval and related spaces. Most importantly, you are excited to be part of a mission-oriented high-growth startup that can create a lasting impact. You Will Conceptualize, develop, and deploy machine learning models that underpin our NLP, retrieval, ranking, reasoning, dialog and code-generation systems. Implement advanced machine learning algorithms, such as Transformer-based models, reinforcement learning, ensemble learning, and agent-based systems to continually improve the performance of our AI systems. Process and analyze large, complex datasets (structured, semi-structured, and unstructured), and use your findings to inf
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