About the Role

At Together.ai, we are building state-of-the-art infrastructure to enable efficient and scalable inference for large language models (LLMs). Our mission is to optimize inference frameworks, algorithms, and infrastructure, pushing the boundaries of performance, scalability, and cost-efficiency.

We are seeking an Inference Frameworks and Optimization Engineer to design, develop, and optimize distributed inference engines that support multimodal and language models at scale. This role will focus on low-latency, high-throughput inference, GPU/accelerator optimizations, and software-hardware co-design, ensuring efficient large-scale deployment of LLMs and vision models.

This role offers a unique opportunity to shape the future of LLM inference infrastructure, ensuring scalable, high-performance AI deployment across a diverse range of applications. If you're passionate about pushing the boundaries of AI inference, we’d love to hear from you!

Responsibilities

Inference Framework Development and Optimization

• Design and develop fault-tolerant, high-concurrency distributed inference engine for text, image, and multimodal generation models.
• Implement and optimize distributed inference strategies, including Mixture of Experts (MoE) parallelism, tensor parallelism, pipeline parallelism for high-performance serving.
• Apply CUDA graph optimizations, TensorRT/TRT-LLM graph optimizations, and PyTorch-based compilation (torch.compile), and speculative decoding to enhance efficiency and scalability.

Software-Hardware Co-Design and AI Infrastructure

• Collaborate with hardware teams on performance bottleneck analysis, co-optimize inference performance for GPUs, TPUs, or custom accelerators.
• Work closely with AI researchers and infrastructure engineers to develop efficient model execution plans and optimize E2E model serving pipelines.

Requirements

Must-Have:

• Experience:
  • 3+ years of experience in deep learning inference frameworks, distributed systems, or high-performance computing.
• Technical Skills:
  • Familiar with at least one LLM inference frameworks (e.g., TensorRT-LLM, vLLM, SGLang, TGI(Text Generation Inference)).
  • Background knowledge and experience in at least one of the following: GPU programming (CUDA/Triton/TensorRT), compiler, model quantization, and GPU cluster scheduling.
  • Deep understanding of KV cache systems like Mooncake, PagedAttention, or custom in-house variants.
• Programming:
  • Proficient in Python and C++/CUDA for high-performance deep learning inference.
• Optimization Techniques:
  • Deep understanding of Transformer architectures and LLM/VLM/Diffusion model optimization.
  • Knowledge of inference optimization, such as workload scheduling, CUDA graph, compiled, efficient kernels
• Soft Skills:
  • Strong analytical problem-solving skills with a performance-driven mindset.
  • Excellent collaboration and communication skills across teams.

Nice-to-Have:

• Experience in developing software systems for large-scale data center networks with RDMA/RoCE
• Familiar with distributed filesystem(e.g., 3FS, HDFS, Ceph)
• Familiar with open source distributed scheduling/orchestration frameworks, such as Kubernetes (K8S)
• Contributions to open-source deep learning inference projects.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $160,000 - $230,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Please see our privacy policy at https://www.together.ai/privacy  

About the Role

We are looking for a Senior Software Engineer to join our ML Infrastructure: Dev Enablement Team. Our mission is to build a frictionless development environment that empowers our researchers and engineers to rapidly innovate on deep learning models for autonomous driving.

We manage a high-scale Cloud Development Environment (CDE) platform that provides standardized, high-performance workspaces for ML development. As we evolve, in this role, you’ll spearhead high-impact initiatives: designing multi-cloud setups to maximize GPU availability, driving deep-level model optimization, and building next-generation Agentic AI toolings. You will play a pivotal role in ensuring our training ecosystem remains cutting-edge, resilient and highly efficient.

What You’ll Be Doing

• Architect Multi-Cloud Solutions: Explore, design, and implement multi-cloud architectures for our ML training platform to increase the availability, scalability, and resilience of high-performance compute resources (GPUs).
• System-Level ML Optimization: Partner closely with ML Researchers to profile and optimize distributed training jobs (PyTorch/DDP). Focus on resolving system-level bottlenecks—such as data loading (I/O), memory management, and network communication overhead—to maximize GPU utilization and training throughput.
• Build Agentic AI Tooling: Design, develop, and enhance Agentic AI tools and systems to automate workflows, streamline the ML lifecycle, and empower developer productivity.
• Scale Core Infrastructure: Drive the continuous development of our core ML infrastructure and existing CDE platform, leveraging Kubernetes to build robust, high-scale distributed solutions.
• Collaborate Cross-Functionally: Partner with ML engineers and data scientists to understand their complex needs, bridging the gap between underlying infrastructure and model development.
• Drive Engineering Excellence: Champion best practices in software engineering, system reliability, and code quality while mentoring junior engineers through high-level system design and code reviews.

What We’re Looking For

• BS or MS in Computer Science or related field
• 5+ years of professional experience in software engineering with strong foundations in distributed systems.
• Expertise with Python or Go or C++
• Solid experience with building on AWS services or other Cloud platforms and container orchestration using Kubernetes.
• Experience with the various stages of the ML development lifecycle
• Strong written and oral communication skills, with a track record of successfully taking ownership of infrastructure components and mentoring junior engineers.

Bonus Points

• Hands-on experience with ML model profiling and performance optimization for distributed training.
• Experience managing or working with high-performance compute resources (GPUs).
• Experience with ML frameworks such as PyTorch or Ray.
• Experience building, integrating, or enhancing Agentic AI systems and LLM-driven developer tools.

At the Riot Singapore Efficiency team, we're driven by innovation and optimization. Our team harnesses the power of Machine Learning approaches and Artificial Intelligence to reimagine the way we build games. By leveraging cutting-edge technology, we aim to streamline development processes, enhance creative workflows, which finally deliver immersive experiences to players around the globe. Join us in pushing the boundaries of what's possible in game development and shaping the future of interactive entertainment.

We are seeking a talented and experienced Data Scientist to join our AI team. As a Senior Data Scientist, you will play a key role in leveraging Machine Learning techniques to drive innovation and efficiency in our game development processes. You will collaborate closely with game teams to accelerate artists' pipelines, streamline workflows, and introduce novel tools aimed at enhancing player experiences.

Responsibilities

• Collaborate on the development and implementation of Machine Learning models aimed at accelerating creative pipeline optimizations, enhancing processes such as content creation, iteration, and integration.
• Work closely with game designers, engineers, and artists to identify opportunities for applying Machine Learning techniques to streamline creative workflows, improve asset generation, and enhance overall efficiency in game development.
• Design and conduct experiments to validate models, measure their impact on creative pipeline optimizations, and drive continuous improvement.
• Stay abreast of the latest advancements in Machine Learning, and gaming technology, and proactively explore innovative approaches to enhancing creative pipeline efficiencies.

Required Skills 

• Master’s or Ph.D. degree in Computer Science, Statistics, Mathematics, or a related field, with a focus on Machine Learning, Data Science, or Artificial Intelligence.
• At least 3 years of extensive experience in applying Data Science techniques to real-world problems, with a proven track record of delivering impactful data science solutions in a fast-paced environment.
• Proficiency in programming languages such as Python, R, C, C++, C#, and experience with libraries and frameworks such as TensorFlow, PyTorch, or JAX.
• Strong understanding of statistical analysis, experimental design, and data visualization techniques.
• Experience working with Generative Models, such as Score-based Diffusion Models, Generative Adversarial Networks (GANs) or Variational Autoencoders (VAEs), to drive creative pipeline optimizations.
• Excellent communication skills, with the ability to effectively communicate complex technical concepts to non-technical stakeholders.
• Leadership experience, including mentoring junior team members, interns and driving cross-functional collaboration, is highly desirable.

Desired Skills 

• Experience working in the gaming industry or a related field is a plus.

For this role, you'll find success through craft expertise, a collaborative spirit, and decision-making that prioritizes the delight of players. We will be looking at your past studies, experience, and your personal relationship with games. If you embody player empathy and care about players' experiences, this could be your role!

Our Perks

• Full relocation support
• Full health insurance for you, your spouse and children
• Open paid time off
• Retirement benefits with company matching
• Life insurance, parental leave, plus short-term and long-term disability
• Play Fund so you can broaden and deepen your knowledge of our players and community through games
• We will double down on your donations of time and money to non-profits

Who We're Looking For

As a Machine Learning Engineer in Delivery, you are an experienced problem solver and technical leader who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple industries, lead technical initiatives, and excel at working directly with customers (and often side-by-side with them on-site) to embed cutting-edge AI models into tools that are useful and used.

You’ve shipped ML systems end-to-end and at scale: you design, build and test reliable, scalable ML data pipelines; you know how to explore and manipulate 3D point-cloud and mesh data to enable geometry-aware modelling; you select the right libraries, frameworks and tools and make pragmatic product decisions that set Delivery up for success. Working at the intersection of data science and software engineering, you translate R&D and project outputs into reusable libraries, tooling and products.

With at least 3 years industry experience (post Masters or PhD) in a commercial, non-research environment, you're ready to not only execute but also lead and mentor others. You're truly excited about taking ownership of complex work streams and guiding teams to success, while continuously improving the systems and solutions you work on to ensure they are practical, impactful and meet the evolving needs of our customers.

This Role 

As a machine learning engineer, you'll work closely with our Data Scientists, Simulation Engineers, and customers to understand and define the engineering and physics challenges we are solving. You will iterate with customers and use your influence to drive decisions around reliable deployment with measurable outcomes.

You'll:

• Own the deployment of ML models and engineering surrogates (e.g., deep learning on CAE/CFD/FEA data, time‑series forecasting, anomaly detection, optimization & control) to customer production environments.
• Communicate results and trade‑offs to senior stakeholders; steer roadmaps and influence product direction with evidence.
• Lead scoping and architecture design for data/ML systems; define success metrics, delivery plans and quality bars.
• Excel at building robust and scalable ML systems, training and inference pipelines and APIs, running both on cloud and on-prem environments. The tech stack you will use for this includes: Python, PyTorch, Pandas, fastAPI, Scipy, Kubeflow, among others.
• Mentor and develop engineers and data scientists; provide technical direction and clear, calm decision‑making under pressure.
• Travel to customer sites in North America, Europe, Asia, Oceania, for an average of 3-4 weeks per quarter, where you'll collaborate closely with customers to build solutions on-site.
• Own the scoping of new projects and work-streams with existing customers and taking part in bringing new customers to PhysicsX.

As an early member of the team, you’ll significantly influence our technical direction and will be involved in shaping future solutions and products, while developing your skills as a technical leader.

Our delivery teams drive innovation to turn AI models into practical solutions - read our blog to learn more about how you’ll contribute to this exciting journey! 

On our Perception team, you have the opportunity to work with world-class ML engineers and research scientists, whose mission is to make self-driving vehicles a reality and to create a positive social impact. Our team works on the tech stack responsible for perceiving the dynamic scenarios, and further tracking and classifying objects around our robo-taxi. We are looking for engineers who are passionate about Level 4 autonomous driving technology, excited by intellectual challenges, and interested in pursuing career growth with a fast-growing company.

What You'll Be Doing:

• Contribute to the development and implementation of advanced perception algorithms for object detection, tracking, classification, and segmentation using camera, lidar, and radar data
• Connect and drive business impact through technology solutions
• Design and implement sensor fusion algorithms to combine data from multiple sensors to create a robust and accurate perception system
• Optimize perception algorithms for real-time performance on embedded hardware
• Collaborate with other engineers and teams to integrate perception systems into larger autonomous systems
• Stay abreast of the latest research and advancements in machine learning and computer vision and apply them to real-world problems
• Productionize and deploy solutions onto autonomous vehicle fleets
• Derive good insight from large data sets from a variety of sources
• Mentor and guide junior engineers on the team

What We're Looking For:

• Masters or Ph.D. in Machine Learning, Computer Science, Robotics, Applied Mathematics, Statistics, Physics or a related field; or equivalent industry experience
• In-depth understanding of common Machine Learning and Deep Learning algorithms
• Experience with designing, training, and analyzing neural networks for at least one of the following applications: object detection, semantic/instance segmentation, visual classification, motion/gesture recognition, sensor fusion, multitask learning, multi-object tracking, and/or end-to-end perception
• Experience with deep learning frameworks such as TensorFlow or PyTorch
• Fluency in Python, including standard scientific computing libraries and Python bindings development experience
• Advanced knowledge of software engineering principles including software design, source control management, build processes, code reviews, testing methods
• Excellent communication and interpersonal skills
• Experience mentoring and leading others

Preferred, but not required:

• Strong programming skills in C++ and/or CUDA programming
• Proven track record of developing and deploying perception systems for autonomous vehicles or robotics
• Experience with embedded systems and real-time optimization, especially in the autonomous driving industry
• Experience with launching ML products from ideation
• Proven track record of publications in relevant conferences (CVPR, ICML, NeurIPS, ICCV, ICL, etc.)
• Experience in deploying models into real-world environments

Mission Summary:

On our Perception team, you have the opportunity to work with world-class ML engineers and research scientists to make self-driving vehicles a reality. The Perception Platform team is central to this mission, operating at the intersection of ML Infrastructure and Perception. We build the foundational frameworks, evaluation pipelines, and tooling that enable our Perception team to scale their work on the tech stack responsible for perceiving the dynamic world around our robo-taxi.

These foundational systems include our large-scale data pipelines,  which are critical for efficient end-to-end ML development (e.g. data transformation, model training, and model evaluation) of our on-car and off-car Perception solutions. It also includes our evaluation and visualization tools, which provide intuitive insights into dataset distributions, model behavior, system performance, and edge-case scenarios. Finally, our active learning loop which continuously selects and incorporates high-value data to improve model accuracy and robustness over time.

What you’ll be doing: 

• Build, lead and manage a high-performing team in the creation, maintenance, and optimization of our internal data, training, and evaluation pipelines specific to perception modelling team.
• Provide technical guidance, mentorship, and career development opportunities to team members
• Define team goals, priorities, and roadmap in alignment with company objectives
• Work closely with ML engineers to proactively identify and resolve technical challenges , while also contributing directly to the implementation of those improvements. This includes troubleshooting and optimizing machine learning workflows for maximum efficiency and performance, architecting and executing cutting-edge technologies/methodologies for accelerating ML development end-to-end from concept to deployment & maintenance.
• Lead design and code reviews, setting a high bar for quality and ensuring the adoption of best practices.
• Foster cross-functional collaboration ensuring alignment with broader organizational goals.

What We’re Looking for:

• 7+ years of professional software engineering experience, with at least 3+ years in a formal or informal leadership or mentorship role.
• BS or MS in Computer Science or a related technical field.
• A passion for remaining hands-on and a proven ability to contribute high-quality, production-level code to a shared codebase.
• Fluency in Python and familiarity with data processing libraries (e.g., NumPy, Pandas)
• Proven experience in backend development and leading the architecture of complex systems.
• A deep understanding of ML or Perception topics to strategically guide pipelines/tooling.
• Demonstrated experience in designing and delivering data visualization tools or internal engineering dashboards that drive insights and action.
• Expert knowledge of software engineering principles, with a track record of leading teams in software design, source control management, build processes, code reviews, and testing methods.
• Excellent communication and interpersonal skills, with the ability to articulate a technical vision and motivate a team

Bonus Points:

• Expertise in concurrency, parallel processing, and database systems to inform architectural decisions.
• Experience with distributed computing frameworks like K8s and Ray.
• A proven track record of developing and deploying Perception systems for autonomous vehicles or robotics.
• A Ph.D. in a relevant field, or equivalent industry experience that demonstrates a commitment to continuous learning.
• Proficiency in modern C++ (C++14/17 or later)
• Experience with building products with current LLMs and MCP protocols.
• Experience with GPU-accelerated data processing.
• Familiarity with Pytorch, TensorFlow or other modern ML development platform
• Experience in project management and a history of successfully delivering complex technical projects.

On our Map Semantics team, you will have the opportunity to work with world-class machine learning (ML) engineers, whose mission is to make self-driving vehicles a reality and to create a positive social impact. The team develops ML models that detect fixed, semantic objects in multi-modal data, enabling mapping and real-time localization.  These objects include lane lines, stoplights, traffic signs and other structures in the built environment.  We are looking for proven technical experts who are passionate about Level 4 autonomous driving technology, excited by intellectual challenges, and interested in pursuing career growth with a fast-growing company.

What You’ll Be Doing:

• Define and execute projects focused on scene understanding to geometrically represent the environment. These representations will enhance the efficiency of our self-driving vehicle’s capability to map roadways and localize itself using both autonomous vehicle and remote sensing data.
• Develop machine learning models to reliably and efficiently detect the built environment using single or multi-modal sensor data including vision, LIDAR, and RADAR
• Productionize and deploy solutions onto autonomous vehicle fleets
• Collaborate with localization, mapping and perception teams to improve  your products’ on-road performance

What We’re Looking for:

• Masters or Ph.D. in Computer Science or a related technical field; or equivalent industry experience
• 7+ years of professional software engineering experience.
• Solid experience in real time 3D Object Detection, Semantic Segmentation or Scene element detection
  Experience working with large scale multi-modal datasets. 
• Experience with deep learning frameworks such as TensorFlow or PyTorch
• Fluency in Python, including standard scientific computing libraries
• Proven track record of designing, developing and deploying ML solutions for autonomous vehicles or robotics
• Advanced knowledge of software engineering principles including software design, source control management, build processes, code reviews, testing methods
• Extensive experience in metrics design and metrics driven technology development 
• Excellent communication and interpersonal skills

Bonus Points:

• Familiarity with multi-view geometry, factor graph optimization / bundle adjustment
• Experience with embedded systems and real-time optimization, especially in the autonomous driving industry
• Remote sensing experience including geospatial coordinate frames, object detection, RPC camera models
• Experience with change detection and updating maps based on newly collected data
• Experience with un/self/semi/weakly-supervised learning techniques
• Strong programming skills in C++ 
• Proven track record of publications in relevant conferences (CVPR, ICML, NeurIPS, ICCV, WACV, AAAI, ICL, etc.)

【The Role】

We are looking for a Machine Learning Engineer with strong experience in large-scale recommendation systems to help build the next-generation social media platform.

You will own critical components of our recommendation stack — including recall, ranking, CTR modeling, and multi-objective optimization — with the goal of driving retention, engagement, and long-term ecosystem growth.

【A Day in the Life】

• Design and deploy scalable recommendation pipelines 
• Develop and optimize CTR/CVR prediction models
• Improve multi-objective ranking strategies (retention, monetization, diversity, long-term value)
• Tackle cold-start challenges for new users and new content
• Run offline experiments and online A/B testing to drive measurable gains
• Collaborate closely with product, engineering, and monetization teams
• Continuously iterate on model performance, latency, and system reliability

【The Impact You’ll Make】

• Improve user retention through intelligent content recommendation
• Drive measurable lift in engagement and monetization metrics
• Build core ranking mechanics beyond incremental model tuning
• Shape the foundation of a scalable, long-term content ecosystem

【Who You Are】

• 3–5 years of experience building production-grade ML systems
• Strong hands-on experience in recommendation systems
• Experience in one or more:
• Recall systems / candidate generation
• Ranking models
• CTR prediction
• Multi-task or multi-objective optimization
• Proficient in Python and ML frameworks (PyTorch, TensorFlow, etc.)
• Strong software engineering fundamentals
• Experience with large-scale data systems and distributed training is a plus
• Experience improving retention or long-term user value is highly valued

【Why Join This Venture】

• Build 0-to-1 systems inside a proven AI powerhouse
• High ownership and direct business impact
• Startup speed with AppLovin-level scale and resources
• Opportunity to shape a new growth engine for the company

AppLovin has become aware of a scam targeting jobseekers with fake “app optimization” and similar roles.  We do not ask our candidates to download apps or make any form of payment(s). AppLovin works with applicants through our Careers page and applovin.com email addresses. If you are contacted through other unofficial channels (such as WhatsApp or Telegram) or asked to download an app or make a payment, these contacts are not legitimate. Confirm the information here and contact us directly with any questions.

 

AppLovin is proud to be an equal opportunity employer that is committed to inclusion and diversity. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status, or other legally protected characteristics. Learn more about EEO rights as an applicant here.

 

If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send us a request at accommodations@applovin.com.

 

AppLovin will consider for employment all qualified applicants with criminal histories in a manner consistent with applicable law.  If you’re applying for a position in California, learn more here.

 

To support an efficient and fair hiring process, we may use technology-assisted tools, including artificial intelligence (AI), to help identify and evaluate candidates. All hiring decisions are ultimately made by human reviewers.

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Please read our Global Applicant Privacy Notice to learn more about how AppLovin processes your personal information. 

 

 

 

 

             

Mission Summary:

We are seeking an experienced and visionary Principle Level Tech Lead Manager to build and lead our new Machine Learning (ML) Acceleration team. This pivotal role will drive the strategy, development, and execution of initiatives aimed at significantly accelerating ML model training. The ultimate goal is to drastically reduce the development cycle for new ML models and enable rapid hot-patching for issues within our deployed autonomous vehicle services.

You will be a hands-on leader, blending deep technical expertise in ML systems and performance optimization with strong leadership and people management skills. You will recruit, mentor, and grow a high-performing team of engineers, fostering a culture of innovation, collaboration, and continuous improvement.

What you'll be doing:

• Team Leadership & Management:
• Build, lead, and manage a high-performing team of ML and infra engineers focused on acceleration.
• Provide technical guidance, mentorship, and career development opportunities to team members.
• Foster a collaborative and inclusive team environment.
• Define team goals, priorities, and roadmap in alignment with company objectives.
  
  
• Technical Strategy & Execution:
• Define the technical vision and strategy for ML acceleration across the organization.
• Identify and evaluate cutting-edge technologies and methodologies for speeding up ML training, including but not limited to data pipeline optimization, large scale distributed training, data loader optimization, hardware acceleration, and model optimization techniques.
• Design, develop, and implement scalable and efficient ML acceleration solutions.
  
  
• Cross-functional Collaboration:
• Collaborate closely with ML research, ML Training platform, and product teams to understand their needs and integrate acceleration solutions seamlessly.
• Communicate complex technical concepts and strategies to both technical and non-technical stakeholders.
• Act as a technical expert and advocate for ML acceleration initiatives across the company.
  
  
• Impact & Measurement:
• Regularly measure and report on the impact of acceleration efforts.
• Continuously seek opportunities for further optimization and innovation.
  
  

What we're looking for:

• Experience:
• Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience
• 8+ years of experience in software engineering, with at least 5+ years focused on Machine Learning systems and model performance optimization.
• 3+ years of experience in a technical lead or management role, with a proven track record of building and leading high-performing teams.
• Extensive experience with large-scale ML model training and deployment, ideally in a production environment.
• Strong understanding of distributed systems and cloud computing platforms (e.g., AWS, GCP, Azure).
  
  
• Technical Skills:
• Deep expertise in ML frameworks such as PyTorch or JAX.
• Proficiency in performance profiling and optimization techniques for Deep Neural Networks.
• Strong programming skills in Python; C++ experience is a plus.
• Knowledge of MLOps principles and practices.
  
  
• Leadership Skills:
• Exceptional leadership, communication, and interpersonal skills.
• Ability to attract, hire, and retain top engineering talent.
• Proven ability to drive complex technical projects from conception to completion.
• Strong problem-solving skills and a proactive, results-oriented mindset.
• Ability to thrive in a fast-paced, dynamic environment.

Mission Summary:

We are looking for a Machine Learning Systems Engineer to join our ML Acceleration team. In this role, you will be responsible for the core systems that enable our researchers to train frontier models at scale, focusing obsessively on speed, cost, reliability, and throughput. You will work at the intersection of machine learning research and high-performance systems engineering. Your work will directly impact our ability to scale large-scale distributed model training and reduce the time-to-convergence for our next generation of models.

What you'll be doing:

• Performance Profiling & Optimization: Utilize profiling tools (e.g., Nsight, PyTorch Profiler) to identify bottlenecks in data loading, gradient computation, and communication. Implement optimizations like kernel fusion, sharding, and tiling to improve step time.
• Distributed Training: Optimize distributed training pipelines using frameworks such as PyTorch Distributed.
• Kernel Development: Design and maintain high-performance GPU kernels in Triton or CUDA for state-of-the-art ML workloads.
• Data Pipeline Engineering: Optimize robust data loading pipelines that maximize training throughput.
  
  

What we're looking for:

• Education: Bachelor’s, Master’s degree, or PhD in Computer Science, Computer Engineering, or a related technical discipline.
• Software Engineering: Strong proficiency in Python.
• ML Frameworks: Extensive hands-on experience with PyTorch.
• ML Knowledge: Experience optimizing machine learning model execution during training and inference, alongside a strong understanding of fundamental machine learning concepts, architectures, and processes.
• Problem Solving: Exceptional analytical and problem-solving skills, with a bias for action and a data-driven approach to technical challenges.

On our Behaviors team, you have the opportunity to work with world-class ML engineers and research scientists whose mission is to make self-driving vehicles a reality and to create positive social impact. The Behaviors team develops ML models that learn how different agents navigate complex real-world traffic scenarios. We leverage these models to set the behavior of our self-driving vehicle, and predict the behavior of other agents such as vehicles and vulnerable road users. We are looking for engineers who are passionate about autonomous driving, excited by intellectual challenges,  and interested in pursuing career growth with a fast-growing company.

What You’ll Be Doing:  

You drive project-level impact to make our autonomous vehicles operate at superhuman capabilities for comfortable, safe driving. Daily, you will:

Senior Engineer:

• Prototype, evaluate, implement, and iterate on solutions
• Familiar with state of the art solutions and systems for autonomous vehicles
• Productionize and deploy solutions onto autonomous vehicle fleets
• Collaborate with team members to achieve project goals and milestones

Staff Engineer:

• Define and influence the direction of the team, organization, and/or department.
• Advise leaders on technology problems and solutions
• Connect and drive business impact through technology solutions 
• Formulate problems, architect solutions, and design processes
• Prototype, evaluate, implement, and iterate on solutions
• Pioneer research into state of the art solutions and systems for autonomous vehicles
• Productionize and deploy solutions onto autonomous vehicle fleets
• Mentor and grow junior and experienced engineers and researchers
• Help create and reinforce a culture of inclusion, innovation, and excellence

What We’re Looking For:

• BA, Masters or PhD in Machine Learning, Computer Science, Applied Mathematics, Statistics, Physics or a related field; or equivalent industry experience
• In-depth understanding of common Machine Learning and Deep Learning algorithms
• Experience designing, training, and analyzing neural networks for at least one of the following applications: object detection, semantic/instance segmentation, visual classification, motion/gesture recognition, sensor fusion, multitask learning, motion prediction, and/or multi-object tracking
• Advanced knowledge of software engineering principles including software design, source control management, build processes, code reviews, testing methods 
• Fluency in Python, including standard scientific computing libraries and Python bindings development experience
• Experience with PyTorch or other deep learning frameworks
• Experience working with large data sets and deriving insights from data

Senior Engineer:

• Strong track record of tackling less well-defined problems, and executing efficiently to deliver the successful outcome
• Experience mentoring and collaborating with others

Staff Engineer:

• Effectiveness at leading and executing large, complex technical initiatives 
• Strong track record of tackling ambiguous problems, creating clarity from it, and driving it to successful outcomes

Bonus Points:

• Proven track record of publications in relevant conferences (CVPR, ICML, NeurIPS, ICCV, ICLR, etc.)
• PhD in machine learning, computer vision, or robotics vision
• Experience working on autonomous vehicles, or related fields
• Experience in deploying models into real-world environments
• Strong programming skills in C++ and/or CUDA programming

About WPP Media  

WPP is the trusted growth partner for the world’s leading brands. With exceptional talent, trusted data and intelligence, and world-class partnerships – all united by our pioneering agentic marketing platform, WPP Open – we help clients navigate change, capture opportunity, and deliver transformational growth.   

WPP Media is WPP's AI-driven media operating unit, bringing together media, data, and partnerships to deliver creative personalisation at scale. Connected through WPP Open and powered by Open Intelligence, clients see exactly where, how, and why their media investment is working.  

For more information, visit wppmedia.com. 

 Role Summary and Impact 

The Media Futures Group AI Squad is a small, agile, and autonomous innovation team dedicated to charting the course for AI transformation across APAC for one of WPP’s most important and strategic global technology clients. 
 
By seamlessly integrating AI across media, creative, and production, this cross-functional squad delivers cutting-edge innovation and pioneering work to deliver more effective and efficient business outcomes. 
 
The team’s mission is to solve specific business challenges by delivering demonstrable proof of AI-enabled marketing improvements, providing strategic guideposts for the broader organization. 
 
Utilizing best-in-class tools like WPP Open and Gemini, you will innovate and deliver award-winning creative ideas while building, testing, and scaling solutions that enhance effectiveness, efficiency, and execution for our clients. 

 The AI Solutions Engineer serves as the master builder executing the construction. This highly technical role provides the dedicated, hands-on development support required to forcefully move theoretical architectural visions out of isolated testing environments and into highly secure, Google-approved, enterprise-grade production infrastructures. The AI Solutions Engineer bridges the critical, often perilous gap between a fragile, locally hosted prototype and a highly scalable, robust organizational tool capable of withstanding massive global traffic. 

Responsibilities 

• API & UI Development: Construct complex backend Application Programming Interface (API) connections and develop the secure user interfaces absolutely necessary to bridge the proprietary WPP Open platform with localized campaign tools and highly guarded client data lakes. 

• Live Deployment & Debugging: Execute rapid debugging, performance analysis, and troubleshooting of both machine learning models and underlying cloud infrastructure in real-time to prevent catastrophic performance degradation or service outages during live campaign sprints. 

• Security & Compliance: Strictly document the deployed technical architecture upon the conclusion of active campaigns. Solidify security protocols and data pipelines to ensure absolute compliance with enterprise risk standards and global data privacy regulations. 

• Codebase Handover: Facilitate the seamless handover of the finalized codebase to centralized, operations-driven technology teams, ensuring pristine code quality, proper containerization, and long-term deployment readiness. 

Skills and Experience 

• A minimum of 5 years of applied experience in software engineering, highly technical support, or complex solutions engineering. 

• At least 2 years focused exclusively on deploying machine learning (ML) or natural language processing (NLP) applications in live commercial environments. 

• Exceptional coding and scripting capabilities, primarily utilizing Python, Java, C++, or Go. 

• Deep, academic understanding of data structures, complex algorithms, and object-oriented software design principles. 

• Proven, hands-on experience troubleshooting, debugging, and reproducing obscure issues within advanced machine learning frameworks, specifically TensorFlow, Keras, and PyTorch. 

• Extensive operational experience navigating public cloud services, specifically Google Cloud Platform (GCP) components such as Kubernetes, Compute Engine, and Apache Beam. 

• Thorough understanding of computer networking, peering with private clouds, managing highly distributed systems, and Git version control. 

Key Competencies 

• Vertex MLOps & Cloud Infrastructure Deployment: Capable of establishing robust, automated machine learning pipelines using Vertex AI Pipelines and Google Cloud Platform components like Kubernetes and Compute Engine. Must ensure that generative AI tools are properly containerized to scale securely and withstand massive global traffic during live campaigns. 

• Vertex AI Mastery: Deep, hands-on proficiency with Google Cloud's Vertex AI platform as the exclusive, mandated environment for model deployment. Capable of navigating the Vertex Model Garden, configuring foundational models (like Gemini), and executing parameter-efficient fine-tuning for specific campaign needs 

• Secure RAG & Grounding Pipeline Engineering: Expert ability to build complex Retrieval-Augmented Generation (RAG) architectures within Vertex AI. Must demonstrate high technical acumen in securely connecting generative models to highly guarded, proprietary enterprise data lakes and Customer Data Platforms without exposing PII or violating data governance. 

• Rapid Problem-Solving: Ability to diagnose and repair code-level pipeline failures or UI breakdowns under the extreme pressure of a live campaign sprint. 

• Extreme Psychological Resilience: Thriving in highly volatile, fast-paced deployment environments where prototype code must be hardened instantly. 

Life at WPP Media & Benefits  

Our passion for shaping the next era of media is powered by our commitment to Be Extraordinary, investing in our employees to inspire transformational creativity. We also Lead Optimistically, firmly believing in and Championing Growth and Development for every individual. This commitment allows WPP Media employees to leverage the extensive global WPP Media & WPP networks to pursue their passions, build vital professional connections, and learn at the cutting edge of marketing and advertising.  

We Create an Open environment built on trust and respect, where everyone feels they belong and has opportunities to progress. This inclusive culture is fostered through a variety of employee resource groups and frequent in-office events showcasing team wins, sharing thought leadership, and celebrating holidays and milestone events. Our comprehensive benefits package reflects this commitment, including competitive medical, vision, and dental insurance, significant paid time off, preferential partner discounts, and employee mental health awareness days.    

WPP Media is an equal opportunity employer and considers applicants for all positions without discrimination or regard to characteristics. We believe the best work happens when we're together, fostering creativity, collaboration, and connection in this open and supportive environment. That's why we’ve adopted a hybrid approach, with teams in the office around four days a week. If you require accommodations or flexibility, please discuss this with the hiring team during the interview process.  

Please note that while our philosophy is the same across WPP, benefits may vary by office/country. 

#LI-Regional

We are seeking an innovative and experienced Embodied AI Researcher, focusing on the development and application of foundation models in robotics. The successful candidate will contribute to cutting-edge research, designing models and experiments that advance the field of robotics through deep learning and zero-shot generalization.

Responsibilities:

• Train foundation models for robotics, utilizing architectures similar to RT-X.
• Align text-based reasoning processes with low-level robotic control policies.
• Design and conduct experiments to evaluate zero-shot generalization in robotic systems.
• Collaborate with interdisciplinary teams to integrate AI models into practical robotic applications.
• Document and present research findings at internal and external conferences.

Qualifications:

• PhD or equivalent research experience in Deep Learning and Robotics.
• Proven track record of publications in top-tier conferences such as CoRL, ICRA, and NeurIPS.
• Practical experience with imitation learning and behavior cloning techniques.
• Strong programming skills in Python and familiarity with machine learning frameworks such as TensorFlow or PyTorch.
• Excellent problem-solving skills and the ability to work independently and as part of a team.

We are seeking a highly skilled LLM Pre-training & Distributed Systems Engineer. This role is essential for orchestrating large-scale machine learning training runs and optimizing  distributed infrastructure. The ideal candidate will have a deep understanding of GPU clusters and extensive experience in system engineering to ensure efficient and reliable training processes.

Responsibilities:

• Orchestrate distributed training runs across 1,000+ GPUs using PyTorch, DeepSpeed, or Megatron-LM.
• Optimize networking (InfiniBand/RDMA) and memory management to prevent out-of-memory errors.
• Automate checkpointing and failure recovery during month-long training runs.

Required Skills:

• Deep expertise in 3D parallelism (Data, Tensor, Pipeline).
• Experience managing SLURM or Kubernetes-based GPU clusters.
• Strong systems engineering background (C++, CUDA, Python).

Who We're Looking For

As a Principal Machine Learning Engineer in Delivery, you are an experienced problem solver and technical leader who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple industries, lead technical initiatives, and excel at working directly with customers (and often side-by-side with them on-site) to embed cutting-edge AI models into tools that are useful and used.

You’ve shipped ML systems end-to-end and at scale: you design, build and test reliable, scalable ML data pipelines; you know how to explore and manipulate 3D point-cloud and mesh data to enable geometry-aware modelling; you select the right libraries, frameworks and tools and make pragmatic product decisions that set Delivery up for success. Working at the intersection of data science and software engineering, you translate R&D and project outputs into reusable libraries, tooling and products.

With at least 3 years industry experience (post Masters or PhD) in a commercial, non-research environment, you're ready to not only execute but also lead and mentor others. You're truly excited about taking ownership of complex work streams and guiding teams to success, while continuously improving the systems and solutions you work on to ensure they are practical, impactful and meet the evolving needs of our customers.

This Role 

As a Principal MLE, you'll work closely with our Data Scientists, Simulation Engineers, and customers to understand and define the engineering and physics challenges we are solving. You will iterate with customers and use your influence to drive decisions around reliable deployment with measurable outcomes.

You'll:

• Own the deployment of ML models and engineering surrogates (e.g., deep learning on CAE/CFD/FEA data, time‑series forecasting, anomaly detection, optimization & control) to customer production environments.
• Communicate results and trade‑offs to senior stakeholders; steer roadmaps and influence product direction with evidence.
• Lead scoping and architecture design for data/ML systems; define success metrics, delivery plans and quality bars.
• Excel at building robust and scalable ML systems, training and inference pipelines and APIs, running both on cloud and on-prem environments. The tech stack you will use for this includes: Python, PyTorch, Pandas, fastAPI, Scipy, Kubeflow, among others.
• Mentor and develop engineers and data scientists; provide technical direction and clear, calm decision‑making under pressure.
• Travel to customer sites in North America, Europe, Asia, Oceania, for an average of 3-4 weeks per quarter, where you'll collaborate closely with customers to build solutions on-site.
• Own the scoping of new projects and work-streams with existing customers and taking part in bringing new customers to PhysicsX.

As a senior member of the team, you’ll significantly influence our technical direction and will be involved in shaping future solutions and products, while developing your skills as a technical leader.

Our delivery teams drive innovation to turn AI models into practical solutions - read our blog to learn more about how you’ll contribute to this exciting journey! 

Job Description

We are seeking a Portfolio Manager (PM) to lead our top-level capital allocation for our crypto portfolio. You will not just manage a book; you will design and execute the "Ensemble Strategy" that dictates how capital flows between strategies and emerging venues. Your mission is to engineer a "Weather-Proof" portfolio that extracts idiosyncratic alpha from disparate markets while maintaining a strictly controlled risk profile.

Responsibilities

• Dynamic Asset Allocation: Oversee the deployment of capital across the multi-strategies
• Ensemble Optimisation: Build and maintain quantitative frameworks (Risk Parity, Mean-Variance, or Bayesian models) to determine optimal weights based on real-time volatility and correlation.
• Regime-Based Hedging: Utilize Prediction Markets and FX to hedge tail risks and macro shifts impacting the core Crypto portfolios.
• Risk Budgeting: Define and monitor VaR, Stress Tests, and Drawdown limits for individual strategy sleeves.
• Cross-Asset Research: Identify "Lead-Lag" relationships—e.g., how movement in the US Dollar (DXY) or Treasury yields impacts Crypto liquidity and Commodity pricing.

Requirements

• Experience: 5-10 years in a Senior Quantitative Allocation role at a fully systematic multi-strat hedge fund, prop shop, or family office.
• Multi-Asset Mastery: Proven track record managing risk across different systematic strategies. Experience in Prediction Markets (Polymarket, Kalshi) or Event-Driven Trading is a significant plus.
• The Stack: Expert proficiency in Python (NumPy, Pandas, PyTorch/TensorFlow) and SQL/KDB+.
• Quantitative Depth: Mastery of portfolio construction mathematics, including covariance matrix estimation and L^2 regularization.
• Education: Advanced degree (Masters/PhD) in Mathematics, Physics, Computer Science, or Financial Engineering.

Who You Are

• The Aggregator: You don't just look for "good trades"; you look for how trades fit together to improve the fund's overall Information Ratio.
• The Risk-First Thinker: You understand that in a levered multi-asset environment, correlation is the silent killer.
• The Adaptable Architect: You are comfortable transitioning from the 24/7 volatility of Crypto to the structural nuances of the Commodities curve and the binary outcomes of Prediction Markets.

CSQ427R172

Mission

The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. 

The impact you will have:

• Develop cutting-edge GenAI solutions, incorporating the latest techniques from our Mosaic AI research to solve customer problems
• Own production rollouts of consumer and internally facing GenAI applications
• Serve as a trusted technical advisor to customers across a variety of domains
• Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally
• Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap 

What we look for:

• Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy
• Expertise in deploying production-grade GenAI applications, including evaluation and optimizations 
• Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools, i.e. pandas, scikit-learn, PyTorch, etc.
• Experience building production-grade machine learning deployments on AWS, Azure, or GCP
• Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience
• Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike
• Passion for collaboration, life-long learning, and driving business value through AI
• [Preferred] Experience using the Databricks Intelligence Platform and Apache Spark™ to process large-scale distributed datasets
• We require fluency in English and have a preference for candidates who also speak Mandarin

Jump Trading Group is committed to world class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incenting collaboration and mutual respect. At Jump, research outcomes drive more than superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.

Our AI team is a central R&D group comprised of quantitative researchers, engineers, and ML experts leading LLM research and applications at Jump. Our mission is to combine emerging techniques and models with original research to generate signals from unstructured data.

What You’ll Do: 

We are seeking research scientists with a demonstrated ability to apply machine learning to achieve state-of-the-art capabilities in complex and challenging domains. The ideal person for this role will be capable of leading an open-ended research project from concept to production: finding compelling problems well suited to current and projected LLM capabilities, collaborating extensively with trading teams to understand requirements and constraints, and continuously improving model design, tools, and infrastructure. Potential projects may target any area of the quantitative research process with the potential for firmwide application. We believe that successful research efforts require a fluid mix of skills including ML expertise, engineering pragmatism, and market intuition, and welcome all candidates who can demonstrate brilliance in one area, competence in a second, and enthusiasm for the third.

Other duties as assigned or needed.

Skills You’ll Need:

• 5+ year track record of creating ML systems with real metrics & impact in industry and/or academia
• Strong general ML background with some exposure to language modeling architectures (e.g. transformers, SSMs)
• Solid development skills in Python and/or C++
• Familiarity with ML libraries/frameworks such as PyTorch (preferred), TensorFlow, and/or JAX
• Intellectual curiosity, versatility, and originality combined with a pragmatic outlook
• Ability to reason through quantitative problems and communicate effectively with trading researchers
• Reliable and predictable availability

Bonus Points

• Experience with HPC and distributed large model training
• Experience with GPU performance optimization (CUDA or ROCm)
• Experience with end-to-end model development, especially in LLMs
• Prior academic publications and/or contributions to open-source AI research
• Strong opinions on best practices in ML research, tooling, and/or infrastructure

Role

As a Senior Robotics Software Engineer in Sensor-Based Control and Robot Learning, you will develop and integrate advanced control strategies and Machine Learning (ML) policies within Intrinsic’s Realtime Robot Control stack. You will drive the deployment of visual servoing and force-control skills in real-world manufacturing settings, focusing on dexterous, contact-rich assembly tasks. You will be responsible for the full development lifecycle: designing controllers, ensuring scalable hardware integration, conducting large-scale experiments, and optimizing for cycle times and resource usage to meet rigorous industrial standards.

How your work moves the mission forward

• Develop visual servoing and interaction control loops to solve high-precision insertion and assembly tasks.
• Implement sensor fusion and time-synchronization algorithms for multi-modal, sensor-based robot control.
• Take ownership of the full experimentation cycle, regularly running trials on industrial hardware to evaluate algorithmic changes and collect high-quality training data.
• Propose and build modular components for our kinematics, state estimation, and control stacks to improve robustness in contact-rich environments.
• Analyze logs and telemetry from diverse sensor sources to identify failure modes and influence the technical roadmap.
• Optimize the real-time execution framework for learned manipulation models within the Intrinsic platform.

Skills you will need to be successful

• Bachelor’s or Master’s degree in Computer Science, Robotics, or a related field (or equivalent professional experience).
• 5+ years of professional software development experience in C++ within robotics or mechatronic systems.
• Proven practical experience testing and iterating on physical robotics hardware integrated with vision and sensing systems.
• Deep technical knowledge of numerical optimal control, robot motion optimization and sensor-based robot control
• Experience working closely with partners and cross-functional teams in a fast-paced environment.
• Business fluency in English.

Skills that will differentiate your candidacy

• PhD in Robotics, Computer Science, or a related field desired
• Track-record of outstanding academic contributions in the field
• Signal processing expertise in time synchronization, state estimation, and data fusion.
• Experience running ML model inference on on-prem hardware within soft-realtime loops.
• Cloud Infrastructure: Familiarity with cloud databases and cloud compute workflows.
• Proficiency in JAX, Python, TensorFlow or PyTorch.

Job Description

We are seeking a Research Engineer to lead the development and deployment of novel applications, leveraging Google’s generative AI models. This role focuses on rapidly developing new features, and working across partner teams to deliver solutions, and maximize impact for Google & top Google customers. You will be instrumental in translating cutting-edge AI research into real-world products, and demonstrating the capabilities of latest generation models. We are looking for engineers with a strong track record of building and shipping software, ideally with experience in early-stage environments where they have contributed to scaling products from initial concept to production. The ideal candidate will be motivated by the opportunity to drive product & business impact.

This role requires a strong software engineering foundation and a passion for building and iterating on software products, using state-of-the-art GenAI tools. We are looking for engineers who thrive in fast-paced environments and have a proven ability to deliver high-quality code. Experience in prototyping, building, and scaling software is essential. We particularly value experience in early-stage or startup environments, where engineers take ownership and drive product development from the ground up.

Job responsibilities

• Design and develop scalable software applications leveraging generative AI models.
• Rapidly prototype new features and iterate based on evaluation results.
• Collaborate with researchers and product managers to translate research advancements into tangible product features.
• Optimize software performance and ensure reliability of deployed applications.
• Contribute to the development of best practices for building and deploying generative AI applications.
• Lead the architecture and development of new products & features from 0 to 1.

Minimum qualifications:

• A bachelor degree in computer science, electrical engineering or equivalent experience.
• 8 years of experience in software development with one or more programming languages (e.g., Python) and with data structures/algorithms.
• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
• 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, evaluation, data processing, debugging, and fine-tuning), with expertise in areas such as media generation or reinforcement learning.

Preferred qualifications:

• Experience with generative AI models and applications.
• Contributions to open-source projects.
• Experience with front end development.
• Experience in rapidly developing and shipping software products in a fast-paced, customer-facing startup-like environment, demonstrating adaptability to changing priorities.
• Experience with cloud computing platforms and infrastructure (e.g., Google Cloud Platform, AWS, Azure).
• Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Hugging Face, etc.

Role

As a Robotics Software Engineer specializing in Robot Learning and Manipulation, you will drive the design, training, validation and deployment of contact-rich manipulation skills for real-world manufacturing. Your focus will be on solving dexterous, contact-rich assembly tasks. You will develop and integrate advanced sensor-based control strategies and Machine Learning (ML) policies within the Intrinsic Robot Control stack, managing the full model lifecycle - from architecture, large-scale data collection and training to validation, deployment and cycle-time optimization - to meet rigorous industrial standards.

How your work moves the mission forward

• Develop, train, and deploy multi-modal feedback- and interaction controllers to solve high-precision insertion and assembly tasks.
• Lead the AI manipulation model lifecycle, conducting regular trials on industrial hardware to evaluate algorithmic changes and curate high-quality training datasets.
• Architect and build modular components for reinforcement learning and imitation learning, continuously seeking to improve the robustness of contact-rich assembly tasks.
• Stress-test and optimize the real-time execution framework for learned manipulation models within the Intrinsic platform.

Skills you will need to be successful

• PhD or equivalent professional experience in Robot Learning and AI Manipulation (e.g., Applied RL, Visuomotor Policy Learning, Vision-Language-Action models).
• 2 years of professional experience in C++ and Python, with a proven track record of shipping production-quality code.
• ML Frameworks: Deep expertise with JAX, TensorFlow, or PyTorch.
• Hardware Experience: Direct experience testing and iterating on physical robots integrated with vision and force-torque sensors.
• Operational Grit: A desire to spend significant time in the lab, managing hardware experiments and troubleshooting physical-world edge cases.
• Communication: Business fluency in English.

Skills that will differentiate your candidacy

• Multimodal Perception and Control: Expertise in integrating tactile/force sensing and computer vision  for contact-rich tasks.
• Hardware Experience: Direct experience testing and iterating on physical robot manipulators integrated with vision and force-torque sensors.
• Large-Scale Training: Proficiency in training on massive multimodal datasets and managing cloud-based training workflows (e.g. Argo).
• Infrastructure: Experience with cloud-based training (Argo) and deploying inference on the edge.
• Customer Focus: Willingness to travel internationally to analyze customer use cases and deploy solutions under ambitious timelines.

Job Description

We are seeking a Technical Lead Manager (TLM) to lead the development and deployment of novel applications, leveraging Google’s generative AI models. This role focuses on rapidly developing new features, and working across partner teams to deliver solutions, and maximize impact for Google & top Google customers. You will be instrumental in translating cutting-edge AI research into real-world products, and demonstrating the capabilities of latest generation models. We are looking for a TLM with a strong track record of building and shipping software, and leading engineering teams, ideally with some experience in early-stage environments, where you may have contributed to scaling products from initial concept to production. The ideal candidate will be motivated by the opportunity to drive product & business impact, and develop strong relationships with research teams.

This role requires a strong software engineering foundation, a passion for building and iterating on software products, and proven leadership skills. We are looking for a TLM who thrives in fast-paced environments, and has the proven ability to deliver high-quality code & guide a team to success. Experience in end-to-end development is essential, as is the ability to mentor and develop junior engineers. We particularly value experience in early-stage or startup environments, where managers take ownership and drive product development from the ground up.

Job responsibilities

• Lead a team in the design and development of scalable software applications leveraging generative AI models.
• Guide the team in rapidly developing new features and iterating based on evaluation results.
• Collaborate with researchers and product managers to translate research advancements into tangible product features.
• Oversee the optimization of software performance and ensure the reliability of deployed applications.
• Champion the development of best practices for building and deploying generative AI applications.
• Lead the architecture and development of new products & features from 0 to 1.
• Mentor and develop team members, fostering a collaborative and high-performing environment.
• Partner with PM team to qualify & size new project opportunities.

Minimum qualifications:

• A bachelor degree in computer science, electrical engineering or equivalent experience.
• 8 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
• 5 years of experience in minimum of one ML field (eg. media generation, reinforcement learning, infrastructure etc.)
• 7+ years of experience leading technical projects and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning), including at least 5 years of experience in a people leadership role overseeing and guiding technical teams.

Preferred qualifications:

• Experience with generative AI models and applications.
• Contributions to open-source projects.
• Experience with front-end development.
• Proven experience in rapidly developing and shipping software products in a fast-paced, customer-facing startup-like environment, demonstrating adaptability to changing priorities.
• Experience evaluating model performance, analyzing results, and implementing improvements.
• Experience with cloud computing platforms and infrastructure (e.g., Google Cloud Platform, AWS, Azure).
• Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Hugging Face, etc.

Jump Trading Group is committed to world class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incentivizing collaboration and mutual respect. At Jump, research outcomes drive more than superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.

Our trading teams are each comprised of a dynamic group of traders, quantitative researchers, and engineers who work together to examine the global markets, seeking to understand the complexities of various traded products and exchanges. They leverage their impeccable statistical analysis and data mining skills, using the results of their research to make forecasts and develop profitable predictive trading models.

-------------------------------
*Candidates should be interested in working in Asia for their full-time job after graduation.

*INTERNATIONAL STUDENTS are encouraged to apply. 
-------------------------------

Who Should Apply?

• We are seeking researchers with a demonstrated ability to apply machine learning to achieve state-of-the-art capabilities in complex and challenging domains. 
• The ideal person for this role will be capable of implementing an open-ended research project from concept to production and continuously improving model design, tools, and infrastructure. 
• Potential projects may target any area of the quantitative research and monetization process. We believe that successful research efforts require a fluid mix of skills including ML expertise, engineering pragmatism, statistics and market intuition.
• No prior knowledge of finance or trading is necessary. We’ll give you the training that you’ll need.
  
• Other duties as assigned or needed.

Skills You'll Need: 

• Creative thinkers who are driven, self-motivated, and eager to solve challenging problems with a pragmatic outlook
• Strong publication record at ICML, ICLR, AAAI, NeurIPS, UAI, KDD, or equivalent and/or contributions to open-source AI research
• Familiarity with ML libraries/frameworks such as PyTorch, TensorFlow, and/or JAX
• Proficiency in Python and/or C++
• Ability to thrive in a collaborative, team-oriented environment
• Ability to reason through quantitative problems and communicate effectively with trading researchers
• Strong general ML background with exposure to modern deep learning techniques and/or language modeling architectures (e.g. transformers, SSMs)
• Reliable and predictable availability required

If you have outstanding skills in math, ML, and programming, and you are curious about the challenge of improving research with daily feedback from competitive markets, we hope you’ll apply.

About the role 

We are seeking an experienced Machine Learning Lead to helm our Machine Learning team. 

In this pivotal role, you will be the engineering architect behind Vulcan’s core AI capabilities. You will act as the nexus between Research, Platform, and Product. Your mission is to translate cutting-edge findings on GenAI threats into robust, production-ready machine learning models that power our GenAI Security Guardrails (Blue Team) and Automated Vulnerability Assessment (Red Team). 

Crucially, you will serve as the bridge between deep tech and business strategy, articulating technical constraints (like FLOPS and latency) to leadership and clients while guiding the engineering direction. 

Key Responsibilities

1. Model Development & Optimization (Training & Fine-tuning):

• Research to Production: Collaborate with the Security Research Team to operationalize new threat detection techniques. They identify the "what" (e.g., new prompt injection patterns); you determine the "how" (model architecture, training strategy). 
• Fine-tuning & Adaptation: Lead the fine-tuning of Language Models (e.g., using LoRA/PEFT) to optimize for our supported muti-lingual languages and specific security intents.
• Multimodal Readiness: Prepare the system for Multimodal (Text + Image/Audio) capabilities. Evaluate and implement models to detect visual prompt injections and non-textual threats as the product evolves. 

2. MLOps& Data Infrastructure: 

• Enhance & Scale MLOps: Take ownership of our existing ML pipelines. Focus on optimizing and scaling CI/CD/CT workflows to improve training efficiency and deployment velocity. 
• Data Governance: Implement and enforce rigorous Data Versioning strategies (e.g., DVC) to ensure complete reproducibility of model artifacts and datasets.
• Monitoring & Reliability: Maintain rigorous monitoring for model drift and performance, ensuring high reliability in a production security environment.

3. Cross-Functional Implementation & Leadership:

• Platform Collaboration: Work closely with the Platform Engineering Team to integrate ML models into the broader product architecture. Ensure seamless interaction between model inference services and the main platform logic. 
• Team Leadership: Lead and mentor Machine Learning Engineers, fostering a culture of engineering rigor, code quality, and operational excellence.
• Resource Management: Manage GPU resources and compute budgets effectively for both training and inference workloads. 

4. Technical Strategy & Stakeholder Management:

• Translating Tech to Business: Act as the technical voice of the ML team. You must effectively explain complex ML concepts (e.g., FLOPS, quantization trade-offs, model latency vs. accuracy) to executive leadership and clients. 
• Cost-Benefit Analysis: Justify compute resource investments. Articulate the trade-off between infrastructure costs (GPU hours) and performance gains to non-technical stakeholders. 

Qualifications

• Experience: 5+ years in Machine Learning Engineering, with specific experience in leading technical projects or mentoring engineers.
• Communication & Business Acumen: Exceptional ability to distill complex technical topics (e.g., compute complexity, infrastructure costs) into clear, business-relevant insights for decision-makers.
• MLOps Proficiency: Proven experience in optimizing ML pipelines and infrastructure. Familiarity with tools like MLflow, Kubeflow, Airflow, and Data Versioning tools (DVC, etc.).
• Engineering First: Proficient in Python, Docker, and Kubernetes. You treat ML models as software artifacts that need testing and version control.
• NLP & LLM Expertise: Experience with Transformer architectures, Embeddings, and LLM fine-tuning. Familiarity with frameworks like PyTorch, Hugging Face, and vLLM.
• Language Support: Experience processing or fine-tuning models for multi-lingual environments. 

Nice to Have

• Multimodal Expertise: Experience working with Multimodal models (Image-to-Text, Text-to-Image, VLMs like CLIP, LLaVA).
• Security Awareness: Understanding of GenAI security threats (e.g., Prompt Injection).
• High-Performance Computing: Experience optimizing inference speed (quantization, distillation, vLLM) for real-time applications.
• Vector Database: Experience with Vector DBs for RAG applications. 

Why Join Us? 

• Innovative Environment: Be part of a company at the forefront of technology to provide security in GenAI, with opportunities to work on groundbreaking projects. 
• Growth Opportunities: Take your career to new heights with our career development programs and growth-focused culture. 
• Dynamic Team: Join a multi-cultural and dynamic team of dedicated professionals who inspire and support each other. 
• Compensation: Competitive salary and benefits package, commensurate with experience and performance. 

Application Process 

• If you're ready to embark on this exciting journey and contribute to shaping the future of GenAI security, please submit your resume outlining your relevant experience and motivation for applying.
• If you prefer a direct connection or have specific questions about our vision, feel free to reach out to our Co-founder, Alvin Kwock, via LinkedIn. 

We are seeking a seasoned Technical Leader to build and scale the foundational compute infrastructure that powers our state-of-the-art AI models—from multimodal training data pipelines to high-throughput, low-latency video generation.

Responsibilities

You will be the core engineer responsible for building the robust, efficient, and scalable platform that enables our research and production teams to rapidly iterate on HeyGen's generative video models. Your contributions will directly impact model performance, developer productivity, and the final quality of every AI-generated video.

• Optimize GPU Utilization: Design and implement mechanisms to aggressively optimize GPU and cluster utilization across thousands of devices for inference, training, data processing and large-scale deployment of our state-of-art video generation models.

• Develop Large-Scale AI Job Framework: Build highly scalable, reliable frameworks for launching and managing massive, heterogeneous compute jobs, including multi-modal high-volume data ingestion/processing, distributed model training, and continuous evaluation/benchmarking.

• Enhance Observability: Develop world-class observability, tracing, and visualization tools for our compute cluster to ensure reliability, diagnose performance bottlenecks (e.g., memory, bandwidth, communication).

• Accelerate Pipelines: Collaborate closely with AI researchers and AI engineers to integrate innovative acceleration techniques (e.g., custom CUDA kernels, distributed training libraries) into production-ready, scalable training and inference pipelines.

• Infrastructure Management: Champion the adoption and optimization of modern cloud and container technologies (Kubernetes, Ray) for elastic, cost-efficient scaling of our distributed systems.

Minimum Requirements

We are looking for a highly motivated engineer with deep experience operating and optimizing AI infrastructure at scale.

• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

• 5+ years of full-time industry experience in large-scale MLOps, AI infrastructure, or HPC systems.

• Experience with data frameworks and standards like Ray, Apache Spark, LanceDB

• Strong proficiency in Python and a high-performance language such as C++  for developing core infrastructure components.

• Deep understanding and hands-on experience with modern orchestration and distributed computing frameworks such as Kubernetes and Ray.

• Experience with core ML frameworks such as PyTorch, TensorFlow, or JAX.

Preferred Qualifications

• Master's or PhD in Computer Science or a related technical field.

• Demonstrated Tech Lead experience, driving projects from conceptual design through to production deployment across cross-functional teams.

• Prior experience building infrastructure specifically for Generative AI models (e.g., diffusion models, GANs, or large language models) where cost and latency are critical.

• Proven background in building and operating large-scale data infrastructure (e.g., Ray, Apache Spark) to manage petabytes of multi-modal data (video, audio, text).

• Expertise in GPU acceleration and deep familiarity with low-level compute programming, including CUDA, NCCL, or similar technologies for efficient inter-GPU communication.

What HeyGen Offers

• Competitive salary and benefits package.
• Dynamic and inclusive work environment.
• Opportunities for professional growth and advancement.
• Collaborative culture that values innovation and creativity.
• Access to the latest technologies and tools.

HeyGen is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

We are seeking a seasoned Software Engineer to build and scale the foundational compute infrastructure that powers our state-of-the-art AI models—from multimodal training data pipelines to high-throughput, low-latency video generation.

Responsibilities

You will be the core engineer responsible for building the robust, efficient, and scalable platform that enables our research and production teams to rapidly iterate on HeyGen's generative video models. Your contributions will directly impact model performance, developer productivity, and the final quality of every AI-generated video.

• Optimize GPU Utilization: Design and implement mechanisms to aggressively optimize GPU and cluster utilization across thousands of devices for inference, training, data processing and large-scale deployment of our state-of-art video generation models.

• Develop Large-Scale AI Job Framework: Build highly scalable, reliable frameworks for launching and managing massive, heterogeneous compute jobs, including multi-modal high-volume data ingestion/processing, distributed model training, and continuous evaluation/benchmarking.

• Enhance Observability: Develop world-class observability, tracing, and visualization tools for our compute cluster to ensure reliability, diagnose performance bottlenecks (e.g., memory, bandwidth, communication).

• Accelerate Pipelines: Collaborate closely with AI researchers and AI engineers to integrate innovative acceleration techniques (e.g., custom CUDA kernels, distributed training libraries) into production-ready, scalable training and inference pipelines.

• Infrastructure Management: Champion the adoption and optimization of modern cloud and container technologies (Kubernetes, Ray) for elastic, cost-efficient scaling of our distributed systems.

Minimum Requirements

We are looking for a highly motivated engineer with deep experience operating and optimizing AI infrastructure at scale.

• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

• 5+ years of full-time industry experience in large-scale MLOps, AI infrastructure, or HPC systems.

• Experience with data frameworks and standards like Ray, Apache Spark, LanceDB

• Strong proficiency in Python and a high-performance language such as C++  for developing core infrastructure components.

• Deep understanding and hands-on experience with modern orchestration and distributed computing frameworks such as Kubernetes and Ray.

• Experience with core ML frameworks such as PyTorch, TensorFlow, or JAX.

Preferred Qualifications

• Master's or PhD in Computer Science or a related technical field.

• Demonstrated Tech Lead experience, driving projects from conceptual design through to production deployment across cross-functional teams.

• Prior experience building infrastructure specifically for Generative AI models (e.g., diffusion models, GANs, or large language models) where cost and latency are critical.

• Proven background in building and operating large-scale data infrastructure (e.g., Ray, Apache Spark) to manage petabytes of multi-modal data (video, audio, text).

• Expertise in GPU acceleration and deep familiarity with low-level compute programming, including CUDA, NCCL, or similar technologies for efficient inter-GPU communication.

What HeyGen Offers

• Competitive salary and benefits package.
• Dynamic and inclusive work environment.
• Opportunities for professional growth and advancement.
• Collaborative culture that values innovation and creativity.
• Access to the latest technologies and tools.

HeyGen is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Role Overview

We are seeking highly motivated and curious individuals to join our Machine Learning team at Kronos Research. In this role, you will bridge the gap between advanced deep learning and financial markets, designing robust models for medium and high-frequency systematic trading strategies. You will manage the full ML lifecycle, from researching novel architectures to deploying scalable, low-latency models that directly drive trading revenue.

Key Responsibilities

• Feature Engineering: Analyze complex time-series data, orderbook dynamics and trade data to engineer high-signal features
• Deep Learning Architecture: Design and train deep-learning based models (MLP, LSTM, RNN, Transformers, RL agents, etc) tailored for financial trading environments
• Backtesting & Evaluation: Conduct comprehensive backtesting and simulation across various asset classes and exchanges; analyze trade execution and PnL attribution
• Model Deployment: Collaborate with engineering teams to optimize and deploy models into production
• MLOps & Automation: Build and maintain automated pipelines for data ingestion, model retraining, and continuous performance monitoring to streamline the research-to-production workflow

Qualifications

• Strong academic or professional foundation in machine learning, quantitative research, and/or other related STEM fields; open to both experienced candidates and highly-motivated fresh graduates
• Deep understanding of neural network architectures and their application to time-series forecasting
• Proficiency in Python and modern ML frameworks (PyTorch/TensorFlow/Jax); C++ preferred
• Solid command of probability theory, linear algebra and applied statistics
• Strong communication skills and able to articulate technical concepts with clarity
• High level of drive, curiosity and a passion for continuously learning in a fast-paced environment

Driving Product Innovation with Advanced Computer Vision Technology

HeyGen is a dynamic startup at the forefront of revolutionizing video content with state-of-the-art artificial intelligence technology. With a robust track record of growth and a proven business model, we are rapidly carving out a leadership position in the AI-powered video creation industry. We are in search of passionate Research Scientists with a specialization in Computer Vision to propel our mission forward. If you are eager to deploy your advanced skills to disrupt and redefine the video creation and interaction experience, your next big opportunity awaits with us.

Key Responsibilities:

• Applied Innovation and Product Development: Harness your knowledge of generative models, including GANs, Diffusion models, and other multi-modal models, to propel our video creation tools forward. Your role involves translating state-of-the-art research into innovative features that directly enhance our user experience and set our products apart.

• Real-World Solutions: Channel your research capabilities to develop scalable solutions that have a significant impact on our platform, making the video creation process more intuitive, powerful, and accessible to our users.

• Collaborative Engineering and Growth: Engage with a diverse team where collaborative efforts lead to extraordinary outcomes. Embrace an environment that promotes learning, mentorship, and teamwork, furthering both personal development and the advancement of our technology.

Qualifications:

• A Master's or PhD in Computer Science, Engineering, or a related field
• 1-3 years of experience in machine learning and computer vision, demonstrating practical application of generative models and a passion for product-centric innovation.
• Proficiency in Python, with openness to other programming languages and tools as required by project demands.
• Experience with deep learning frameworks such as PyTorch, and a capacity for quickly mastering new technologies.
• A collaborative spirit with a proven track record in a team-based research or development setting.
• A lifelong learner with outstanding problem-solving skills and the ability to communicate effectively in a diverse team environment.

What HeyGen Offers:

• Competitive Salary and Benefits: We offer a salary commensurate with your experience and a comprehensive benefits package that addresses a variety of needs.
• Innovative and Inclusive Work Environment: Our workplace is designed to inspire innovation through collaboration, respect, and mutual support.
• Opportunities for Advancement: We are committed to your professional development, offering extensive opportunities for learning, mentorship, and career growth.
• Dedication to Diversity: HeyGen is an equal opportunity employer, championing a diverse and inclusive team that ensures equal access to opportunities for all members.