Aleph Alpha Research’s mission is to deliver category-defining AI innovation that enables open, accessible, and trustworthy deployment of GenAI in industrial applications. Our organization develops foundational models and next-generation methods that make it easy and affordable for Aleph Alpha’s customers to increase productivity in finance, administration, R&D, logistics, and manufacturing processes.

We are hiring to grow our org in Heidelberg, Germany, and are looking for well-rounded, experienced Senior AI Software Engineers with experience in DevOps/MLOps.

As a Senior AI Software Engineer at Aleph Alpha Research, you'll support research teams in advancing model and algorithm development. You'll own key research infrastructure components including data processing pipelines, testing frameworks, and distributed training software while contributing to projects that deliver novel AI capabilities.

TEAM CONTRIBUTIONS

-Infrastructure & Platform: Maintain cluster/cloud infrastructure, build DevOps/MLOps pipelines, implement SE best practices, collaborate with Data Center and Product Teams. -Data & Distributed Training: Engineer data processing pipelines, develop training software components, support data-heavy tasks. -Research SE: Collaborate with Researchers on model/algorithm development, ablation studies, POCs, and optimizations. Create maintainable codebases for efficient research-to-production transition.

YOUR RESPONSIBILITIES

Design and develop research infrastructure with improved code quality and testing. Support deep learning model development, training, and maintenance. Optimize lower-level code for data processing and research projects. Apply software engineering expertise to research initiatives. Transition AI innovations to real-world applications. Mentor engineers and researchers in development best practices. Work primarily with Python/PyTorch and some Rust for lower-level code.

YOUR PROFILE

5+ years professional experience across the full software development lifecycle. Ability to solve complex problems using scientific approaches. Track record in design/architecture of large-scale systems. Expertise in at least one major programming language (ideally Python). Strong communication skills for conveying complex technical concepts. Bachelor's degree in computer science or related field. Willingness to relocate to or regularly visit Heidelberg, Germany office.

PREFERRED QUALIFICATIONS

Experience integrating complex systems with cross-team collaboration. History designing high-performance, scalable production systems. Research contributions or publications. Experience with systems programming and languages like Rust. Master's degree in relevant field. Experience productizing AI research innovations. Familiarity with NLP tools/frameworks and transformer architectures. Ability to communicate research to diverse stakeholders. Proven application of advanced scientific methods to novel problems.

As a Machine learning engineer, you’ll get to leverage AI and deep learning to thrive in a fast-paced, cutting-edge environment, and apply your advanced degree in a highly impactful role. You will still use your brain to come up with cutting-edge ideas, but instead of working in the abstract you'll make innovations that change the world as soon as you implement them. Turn your passion for machine learning into a rewarding career with Optiver.

What you’ll do We are seeking an exceptional machine learning engineer with a PhD degree to join us. The ideal candidate will have an advanced understanding of neural networks and related machine learning technologies, with experience in implementing and training complex deep learning models. As part of your role, you’ll get to: • Leverage AI and deep learning to thrive in a fast-paced, cutting-edge environment. Collaborate closely with researchers and traders on new experiments, capabilities, and data sources. • Design and implement improvements to optimise researcher productivity and quality. • Blend your own development expertise with the best open-source frameworks and tools. • Leverage cloud infrastructure to solve substantial challenges in computational and data scale. • Drive experimental rigour through repeatable processes on assured data.

What you’ll get You’ll join a culture of collaboration and excellence, where you’ll be surrounded by curious thinkers and creative problem solvers. Driven by a passion for continuous improvement, you’ll thrive in a supportive, high-performing environment alongside talented colleagues, working collectively to tackle the most complex problems in the financial markets. In addition, you’ll receive: • A highly competitive remuneration package. • The opportunity to work alongside best-in-class professionals. • Training, mentorship and personal development opportunities. • Daily breakfast, lunch and snacks. • Gym membership, sports and leisure activities, plus weekly in-house chair massages. • Regular social events, clubs and Friday afternoon drinks.

Who you are • A PhD student, with a graduation date between 2023 and 2025. • Degree in Computer Science, Mathematics, Statistics, or a related field, with a strong focus on machine learning or deep learning. • Proven experience with deep learning frameworks such as TensorFlow, PyTorch, Keras, etc. • Deep understanding of the principles, theories, and concepts underlying machine learning and deep learning technologies, including the design and implementation of neural networks. • Strong programming skills in Python, familiar with data engineering tools and principles. • Experience with GPUs and other hardware accelerators for deep learning. • Excellent problem-solving skills, and the ability to work independently and in teams. • Outstanding communication skills.

Who we are Optiver is a global market maker founded in Amsterdam, with offices in London, Chicago, Austin, New York, Sydney, Shanghai, Hong Kong, Singapore, Taipei and Mumbai. Established in 1986, we are a leading liquidity provider, with close to 2,000 employees in offices around the world, united in our commitment to improve the market through competitive pricing, execution and risk management. How To Apply Ready to take your career to the next level? Apply now via the form below, to work on one of the most exciting trading floors in China mainland. While we enjoy working in bilingual teams, please ensure that the below application materials are submitted in English: • Resume • Academic transcripts, including Bachelors, Master's and PhD, if any

For any other inquiries, please email chinacareers@optiver.com.au.

Privacy Disclaimer Optiver 重视个人信息的保护。请您在提供个人信息给我们之前，认真阅读Optiver China Privacy Notice, 了解我们如何收集及处理您的个人信息。 Personal information protection is of utmost importance to Optiver. Before you provide any personal information to us, we strongly urge you to read our Privacy Policy.

New York

Quantitative Strategies / Technology

Overview

At the D. E. Shaw group, technology is integral to virtually everything we do. We’re seeking exceptional software developers with expertise in generative AI (GAI) to join our team. As a software developer in GAI, you’ll work on innovative projects, leveraging your quantitative and programming skills to advance our GAI initiatives. By making GAI more accessible for both technical and non-technical users across the firm, you’ll drive substantial business impact.

What you’ll do day-to-day

You’ll join a dynamic environment, contributing to our efforts in advancing GAI capabilities. Potential areas of focus include:

• Developing and maintaining shared GAI infrastructure and applications, ensuring firmwide data integration and enhancing software development across the firm.
• Working on foundational building blocks, such as vector databases and LLM gateways, to support AI tools and applications.
• Leveraging state-of-the-art cloud models for scalable and high-availability solutions.
• Scaling the adoption of GAI tools, expanding AI models, and integrating them with internal knowledge sources to drive innovation.
• Collaborating with internal groups and end users to accelerate AI product development and deployment, tailoring solutions to their needs.
• Experimenting with new AI-driven tools and applications, integrating them into various platforms, and facilitating collaboration to enhance the effectiveness of AI applications.
• Working on greenfield projects, which offer opportunities to shape the future of GAI at the firm and make a significant impact.

Who we’re looking for

• We’re looking for candidates who have a strong background in software development and a solid understanding of GAI technologies.
• Successful developers have traditionally been top performers in their academic programs and possess a strong foundation in AI-related projects.
• We welcome outstanding candidates at all experience levels who are excited to work in an inclusive, collaborative, and fast-paced environment.
• The expected annual base salary for this position is 200,000 to 250,000 USD. Our compensation and benefits package includes variable compensation in the form of a year-end bonus, guaranteed in the first year of hire, and benefits including medical and prescription drug coverage, 401(k) contribution matching, wellness reimbursement, family building benefits, and a charitable gift match program.

What you’ll do As a Machine Learning Modelling Engineer, you’ll harness your understanding of AI and deep learning to generate impactful insights and drive innovative new strategies that have the potential to transform global financial markets. By the end of the internship, you'll have deepened your understanding of the quantitative trading industry. Plus, if you've excelled over the summer, you'll receive an offer to return as Graduate Machine Learning Modelling Engineer. You will have the opportunity to: • Leverage AI and deep learning technologies to thrive in a fast-paced, cutting-edge environment. • Collaborate closely with researchers and traders on new experiments, capabilities, and data sources. • Design and implement improvements to optimise researcher productivity and quality. • Blend your own development expertise with the best open-source frameworks and tools. • Utilise computing infrastructure to solve substantial challenges in computational and data scale. • Drive experimental rigor through repeatable processes on assured data.

What you'll get You’ll join a culture of collaboration and excellence, where you’ll be surrounded by curious thinkers and creative problem solvers. Driven by a passion for continuous improvement, you’ll thrive in a supportive, high-performing environment alongside talented colleagues, working collectively to tackle the most complex problems in the financial markets. In addition, you’ll receive: • A highly competitive remuneration package. • Optiver-covered flights and accommodation for the duration of the internship. • The opportunity to work alongside best-in-class professionals. • Training, mentorship and personal development opportunities. • Daily breakfast, lunch and snacks. • Gym membership, sports and leisure activities, plus weekly in-house chair massages. • Regular social events, clubs and Friday afternoon drinks.

Who you are • A PhD student, who is graduating in or after 2026. • Studying a degree in Computer Science, Mathematics, Statistics, or a related field, with a strong focus on machine learning or deep learning. • You’ll have an advanced understanding of neural networks and related machine learning technologies, with experience in implementing and training complex deep learning models. • Proven experience with deep learning frameworks, such as TensorFlow, PyTorch, Keras, etc. • Deep understanding of the principles, theories, and concepts underlying machine learning and deep learning technologies, including the design and implementation of neural networks. • Strong programming skills in Python, familiar with data engineering tools and principles. • Experience with GPUs and other hardware accelerators for deep learning. • Excellent problem-solving skills, and the ability to work independently and in teams. • Outstanding communication skills.

Who we are Optiver is a global market maker founded in Amsterdam, with offices in London, Chicago, Austin, New York, Sydney, Shanghai, Hong Kong, Singapore, Taipei and Mumbai. Established in 1986, today we are a leading liquidity provider, with close to 2,000 employees in offices around the world, united in our commitment to improve the market through competitive pricing, execution and risk management.

How To Apply Ready to take your career to the next level? Apply now via the form below, to work on one of the most exciting trading floors in China mainland. While we enjoy working in bilingual teams, please ensure that the below application materials are submitted in English: • Resume • Academic transcripts, including Bachelors, Master's and PhD, if any

For any other inquiries, please email chinacareers@optiver.com.au.

Privacy Disclaimer Optiver 重视个人信息的保护。请您在提供个人信息给我们之前，认真阅读Optiver China Privacy Notice, 了解我们如何收集及处理您的个人信息。 Personal information protection is of utmost importance to Optiver. Before you provide any personal information to us, we strongly urge you to read our Privacy Policy.

Sunnyvale, CA

Description

Job Purpose As a Research Scientist specializing in Natural Language Processing (NLP) with a focus on large language models and deep learning, your role will be crucial in advancing cutting-edge language processing technologies and contributing to the development of intelligent systems. You will be responsible for a wide range of tasks encompassing research, development, and implementation of NLP solutions, with a particular emphasis on Python coding, machine learning techniques, and deep learning methodologies.

Key Responsibilities: Lead the research of technology for improving the efficiency of Large Language Model (LLM) while performing target capabilities or supporting many capabilities, such as novel architectures and improved pre-training.Design and implement NLP algorithms for model training and prediction, leverage ML infrastructure, and contribute to model optimization and data processing, using Pytorch or other frameworks.Integrate and improve LLM algorithms to work with other models such as computer vision modelsIdentify defined problems/gaps in existing technology and engage other Research teams, stakeholders and leaders to expand efficient LLM technology.Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies.Write up results in design documents, technical reports, and papers for publication.Represent MBZUAI at industry conferences and events, showcasing the institution’s cutting-edge HPC and deep learning capabilities and establishing MBZUAI as a global leader in AI research and innovation.Perform all other duties as reasonably directed by the line manager that are commensurate with these functional objectives.

Academic Qualifications Minimum Master’s in Computer Science, a related technical field, or equivalent practical experience.

Preferred PhD or equivalent research experience in Natural Language Processing

Minimum Professional Experience Experience with state-of-the-art Gen AI techniques and models (e.g., LLMs, Multi-Modal, Large Vision Models) or with Gen AI-related concepts (e.g., language modeling, computer vision).Experience with software development in one or more programming languages (e.g. Python, C++), and with data structures/algorithms.Excellent problem-solving and troubleshooting skills to address complex technical challenges.Effective communication and collaboration skills to work with cross functional teams.Ability to effectively navigate ambiguity.

Preferred Professional Experience Experience leading research efforts and influencing other researchers.Experience with efficiency, modularity or related topics for LLMs.Experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).Experience with design and optimization of algorithms in performance constrained environments (e.g., mobile).Experience in innovative research, contributing to research communities including publishing in forums (e.g., ACL, EMNLP, NAACL, EACL, COLING, ICLR, AAAI, NeurIPS).

Sunnyvale, CA

The MBZUAI Institute of Foundation Models Silicon Valley Lab is a research hub for foundation models.

Job Purpose As a Machine Learning Engineer at the Institute of Foundation Models, your primary responsibility is to develop and implement innovative machine learning models that address real-world challenges, pushing the boundaries of artificial intelligence research. You will collaborate with cross-functional teams to deploy scalable solutions, contributing to MBZUAI’s mission of driving impactful AI discoveries and positioning the institution as a leader in the global AI research community. Your expertise will be key in enhancing the performance of large-scale machine learning models, while supporting the development of transformative AI tools that can influence industries worldwide.

Key Responsibilities

• Collaborate with Research teams to understand technologies, adapting and integrating them into codebase.

• Develop and implement systems to support the lifecycle of machine learning models, such as data preprocessing, pre-training, post-training, evaluation and so on, especially foundation models.

• Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.

• Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).

• Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.

• Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.

• Contribute to research papers and represent MBZUAI at industry conferences and events, showcasing the institution’s cutting-edge HPC and deep learning capabilities and establishing MBZUAI as a global leader in AI research and innovation.

• Perform all other duties as reasonably directed by the line manager that are commensurate with these functional objectives.

Academic Qualifications Minimum Bachelor’s degree or equivalent practical experience.

Preferred Master’s degree or PhD in Computer Science or related technical field.

Minimum Professional Experience

• 3 years of experience in software engineering, including experience with Machine Learning (ML) models, ML infrastructure, Natural Language Processing or Computer Vision.

• 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree in an industry setting.

• 2 years of experience with data structures or algorithms in either an academic or industry setting.

• 2 years of experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning, or natural language processing.

• Excellent problem-solving and troubleshooting skills to address complex technical challenges.

• Effective communication and collaboration skills to work with cross functional teams.

Preferred Professional Experience - 2 years of experience with improving performance during large scale data processing

• Hands-on experience with LLM algorithms, such as Supervised Fine-Tuning (SFT) and Reinforcement Learning with Human Feedback (RLHF).

• Excellent data analysis skills.

San Francisco, CA

About the job The Company

SuperAnnotate is a fast-growing, Series B startup revolutionizing the field of AI-data Infrastructure. We specialize in providing cutting-edge data pipeline solutions for Machine Learning, LLM, and GenAI solutions to large enterprise clients, helping them leverage the power of AI to transform their businesses. SuperAnnotate has a fully customizable platform for building annotation tools and workflows that AI projects demand—while unifying the management of all teams, vendors, and data in one place. We’re very proud to have products that are loved by our customers, resulting in us being listed as the highest-ranked platform on G2.

Role

We seek an outgoing individual passionate about Machine Learning to join our team as a Senior ML Solutions Engineer. In this role, you will be critical in differentiating SuperAnnotate to our enterprise clients by providing in-depth technical expertise and helping them understand how SuperAnnotate can solve their business problems. You are suitable for this role if you love to learn new things and want to stay updated with the most recent trends in AI.

As a Senior ML Solutions Engineer, you will work with clients worldwide to demonstrate and prototype SuperAnnotate's product integrations in domains like large language models, computer vision, natural language processing, and industries like e-commerce, sustainability, and healthcare.

The position is offered with partial remote working as a possibility, allowing flexibility in work location.

Your Day

Working with account executives, lead technical pre-sales efforts to identify customer pain points and demonstrate how SuperAnnotate solutions can achieve desired outcomes Recommend integration strategies, enterprise architectures, and application infrastructure required to implement a complete solution using best practices on SuperAnnotate successfully Drive pilots with enterprise clients, defining success metrics, and proving technical approval on SuperAnnotate integration and adoption across large organizations Provide in-depth machine learning and data expertise to support the technical relationship with SuperAnnotate’s clients, including product and solution briefings and proof-of-concept work Prioritize and ideate new solutions with product development impacting client adoption of SuperAnnotate Demonstrate and prototype ML workflows using SuperAnnotate with clients worldwide Articulate competitive differentiation to highlight SuperAnnotate strengths Build technical credibility and trust with key customer relationships to help SuperAnnotate win business

What Is Needed To Get Started

5+ years of customer-facing experience Experience in a solution or sales engineering environment Strong background in Machine learning and Python Experience driving highly technical pilots/POCs with enterprise customers Great presentation skills Bachelor's degree in Computer Science, Mathematics, Machine Learning, Data Science, or equivalent experience Ability to quickly learn, understand, and work with new emerging technologies, methodologies, and solutions in the Artificial Intelligence technology space Outstanding English writing and verbal skills Great communication skills

Preferred Qualifications

Master's degree in Computer Science, Machine Learning, Data Science, or other technically related fields Experience building Machine learning solutions (e.g., data pipelines, AI systems, LLMs, MLOps, etc.)

Only shortlisted candidates will be contacted for an interview!

Why Work At Nebius

Nebius is leading a new era in cloud computing to serve the global AI economy. We create the tools and resources our customers need to solve real-world challenges and transform industries, without massive infrastructure costs or the need to build large in-house AI/ML teams. Our employees work at the cutting edge of AI cloud infrastructure alongside some of the most experienced and innovative leaders and engineers in the field.

Where We Work

Headquartered in Amsterdam and listed on Nasdaq, Nebius has a global footprint with R&D hubs across Europe, North America, and Israel. The team of over 500 employees includes more than 400 highly skilled engineers with deep expertise across hardware and software engineering, as well as an in-house AI R&D team.

The role

We are looking for a Key Customers Solutions Architect to support key and strategic Nebius GPU Cloud services customers. In this role, you will be a trusted technical advisor, helping clients design, deploy and scale AI solutions while managing large-scale GPU workloads involving hundreds to thousands of GPUs. You will also collaborate with sales and product teams to drive growth and enhance customer satisfaction.

You’re welcome to work in our office in Amsterdam, or remotely from any EU country.

Your responsibilities will include:

• Serve as the primary technical point of contact, troubleshooting and resolving complex AI/ML.
• Guide customers in optimizing GPU performance for ML training and inference workloads, ensuring seamless integration and scalability.
• Partner with the sales team to identify new opportunities, promote the latest products and deliver technical presentations.
• Act as a bridge to product teams, providing customer feedback, relaying feature requests and ensuring alignment with customer requirements.
• Engage with internal and external stakeholders, negotiate solutions and effectively drive alignment to address customer challenges.

We expect you to have:

• Experience: 5+ years in roles like Cloud Solutions Architect, Technical Account Manager or Customer Engineer, with hands-on experience in cloud services and AI/ML workloads.
• Proficiency in Infrastructure as Code (IaC) tools like Terraform and Ansible.
• Experience with Kubernetes and Python programming.
• Solid understanding of GPU computing, including ML training, inference workloads and GPU stacks (e.g., CUDA, OpenCL).
• Customer-centric approach with a proven ability to build trust and foster long-term relationships.
• Strong ability to explain technical concepts to technical and non-technical audiences.
• Written and spoken proficiency in English.

It will be an added bonus if you have:

• Hands-on experience with HPC/ML orchestration frameworks (e.g., Slurm, Kubeflow).
• Experience with deep learning frameworks (e.g., PyTorch, TensorFlow).
• Familiarity with ML tools from NVIDIA, AWS, Azure and Google Cloud providers.
• Strong project management skills, with the ability to prioritize tasks and deliver on deadlines.
• Proven experience mentoring technical teams and driving team growth.
• Expertise in stakeholder negotiation to support problem resolution and ensure seamless collaboration.

What we offer

• Competitive salary and comprehensive benefits package.
• Opportunities for professional growth within Nebius.
• Hybrid working arrangements.
• A dynamic and collaborative work environment that values initiative and innovation.

We’re growing and expanding our products every day. If you’re up to the challenge and are excited about AI and ML as much as we are, join us!

New York

Quantitative Strategies

Overview

Technology is integral to virtually everything the D. E. Shaw group does, which is why we seek exceptional software developers with a range of quantitative and programming abilities. Members of our technical staff collaborate on challenging problems that directly impact the firm’s continued success, utilizing their excellent analytical, mathematical, and software design skills as well as some of the most advanced computing resources in the world. Software developers have the opportunity to be part of an inclusive, collaborative, and engaging working environment.

What you’ll do day-to-day

Specific responsibilities may include formulating statistical models for our computerized trading strategies, developing distributed systems to analyze and react to incoming data in real time, and creating tools for advanced mathematical modeling.

Who we’re looking for

• Successful developers have traditionally been the top students in their programs and have extensive software development experience.
• We welcome outstanding candidates at all experience levels.
• The expected annual base salary for this position is $200,000. Our compensation and benefits package includes substantial variable compensation in the form of a year-end bonus, guaranteed in the first year of hire, a sign-on bonus, a relocation bonus, and benefits including medical and prescription drug coverage, 401(k) contribution matching, wellness reimbursement, family building benefits, and a charitable gift match program.

Location: Singapore

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.

The quantitative trading teams at Jump Trading probe and examine the global markets, seeking to understand the complexities of various traded products and exchanges. They leverage their impeccable statistical analysis, machine learning and deep learning skills, using the results of their research to make forecasts and develop profitable predictive trading models.

What You’ll Do:

We are seeking research scientists with a demonstrated ability to apply deep 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.

Skills You’ll Need:

• At least 5+ years of experience in developing DL systems with measurable impact in industry and/or academia.
• Creative thinkers who are driven, self-motivated, and eager to solve challenging problems.
• Proficiency in Python and/or C++.
• Strong foundation in mathematics and statistics.
• Ability to thrive in a collaborative, team-oriented environment.
• PhD, or Master's degree in Computer Science, Mathematics, (or related subject).
• Strong publications record at ICML, ICLR, AAAI, NeurIPS, UAI, KDD, or equivalent.
• Reliable and predictable availability.
• Excellent written and verbal communication skills in English.