NeurIPS 2025 Career Opportunities

San Jose, CA, USA

Join Adobe as a skilled and proactive Machine Learning Ops Engineer to drive the operational reliability, scalability, and performance of our AI systems! This role is foundational in ensuring our AI systems operate seamlessly across environments while meeting the needs of both developers and end users. You will lead efforts to automate and optimize the full machine learning lifecycle—from data pipelines and model deployment to monitoring, governance, and incident response.

What you'll Do

• Model Lifecycle Management: Manage model versioning, deployment strategies, rollback mechanisms, and A/B testing frameworks for LLM agents and RAG systems. Coordinate model registries, artifacts, and promotion workflows in collaboration with ML Engineers

• Monitoring & Observability: Implement real-time monitoring of model performance (accuracy, latency, drift, degradation). Track conversation quality metrics and user feedback loops for production agents.

• CI/CD for AI: Develop automated pipelines for timely/agent testing, validation, and deployment. Integrate unit/integration tests into model and workflow updates for safe rollouts.

• Infrastructure Automation: Provision and manage scalable infrastructure (Kubernetes, Terraform, serverless stacks). Enable auto-scaling, resource optimization, and load balancing for AI workloads.

• Data Pipeline Management: Craft and maintain data ingestion pipelines for both structured and unstructured sources. Ensure reliable feature extraction, transformation, and data validation workflows.

• Performance Optimization: Monitor and optimize AI stack performance (model latency, API efficiency, GPU/compute utilization). Drive cost-aware engineering across inference, retrieval, and orchestration layers.

• Incident Response & Reliability: Build alerting and triage systems to identify and resolve production issues. Maintain SLAs and develop rollback/recovery strategies for AI services.

• Compliance & Governance: Enforce model governance, audit trails, and explainability standards. Support documentation and regulatory frameworks (e.g., GDPR, SOC 2, internal policy alignment).

What you need to succeed - 3–5+ years in MLOps, DevOps, or ML platform engineering. - Strong experience with cloud infrastructure (AWS/GCP/Azure), container orchestration (Kubernetes), and IaC tools (Terraform, Helm). - Familiarity with ML model serving tools (e.g., MLflow, Seldon, TorchServe, BentoML). - Proficiency in Python and CI/CD automation (e.g., GitHub Actions, Jenkins, Argo Workflows). - Experience with monitoring tools (Prometheus, Grafana, Datadog, ELK, Arize AI, etc.).

Preferred Qualifications - Experience supporting LLM applications, RAG pipelines, or AI agent orchestration. - Understanding of vector databases, embedding workflows, and model retraining triggers. - Exposure to privacy, safety, and responsible AI principles in operational contexts. - Bachelor's or equivalent experience in Computer Science, Engineering, or a related technical field.

Location CAN, ON, Toronto

Description Are you a passionate scientist in the computer vision area who is aspired to apply your skills to bring value to millions of customers? Here at Ring, we have a unique opportunity to innovate and see how the results of our work improve the lives of millions of people and make neighborhoods safer.

As a Principal Applied Scientist, you will work with talented peers pushing the frontier of computer vision and machine learning technology to deliver the best experience for our neighbors.

This is a great opportunity for you to innovate in this space by developing highly optimized algorithms that will work at scale. This position requires experience with developing Computer Vision, Multi-modal LLMs and/or Vision Language Models. You will collaborate with different Amazon teams to make informed decisions on the best practices in machine learning to build highly-optimized integrated hardware and software platforms.

London

Description - Bloomberg’s Engineering AI department has 350+ AI practitioners building highly sought after products and features that often require novel innovations. We are investing in AI to build better search, discovery, and workflow solutions using technologies such as transformers, gradient boosted decision trees, large language models, and dense vector databases. We are expanding our group and seeking highly skilled individuals who will be responsible for contributing to the team (or teams) of Artificial Intelligence (AI) and Software Engineers that are bringing innovative solutions to AI-driven customer-facing products.

At Bloomberg, we believe in fostering a transparent and efficient financial marketplace. Our business is built on technology that makes news, research, financial data, and analytics on over 1 billion proprietary and third-party data points published daily -- across all asset classes -- searchable, discoverable, and actionable.

Bloomberg has been building Artificial Intelligence applications that offer solutions to these problems with high accuracy and low latency since 2009. We build AI systems to help process and organize the ever-increasing volume of structured and unstructured information needed to make informed decisions. Our use of AI uncovers signals, helps us produce analytics about financial instruments in all asset classes, and delivers clarity when our clients need it most.

We are looking for Senior GenAI Platform Engineers with strong expertise and passion for building platforms, especially for GenAI systems.

As a Senior GenAI Platform Engineer, you will have the opportunity to create a more cohesive, integrated, and managed GenAI development life cycle to enable the building and maintenance of our ML systems. Our teams make extensive use of open source technologies such as Kubernetes, KServe, MCP, Envoy AI Gateway, Buildpacks and other cloud-native and GenAI technologies. From technical governance to upstream collaboration, we are committed to enhancing the impact and sustainability of open source.

Join the AI Group as a Senior GenAI Platform Engineer and you will have the opportunity to: -Architect, build, and diagnose multi-tenant GenAI platform systems -Work closely with GenAI application teams to design seamless workflows for continuous model training, inference, and monitoring -Interface with both GenAI experts to understand workflows, pinpoint and resolve inefficiencies, and inform the next set of features for the platforms -Collaborate with open-source communities and GenAI application teams to build a cohesive development experience -Troubleshoot and debug user issues -Provide operational and user-facing documentation

We are looking for a Senior GenAI Platform Engineer with: -Proven years of experience working with an object-oriented programming language (Python, Go, etc.) -Experience with GenAI technologies like MCP, A2A, Langgraph, LlamaIndex, Pydantic AI, OpenAI APIs and SDKs -A Degree in Computer Science, Engineering, Mathematics, similar field of study or equivalent work experience -An understanding of Computer Science fundamentals such as data structures and algorithms -An honest approach to problem-solving, and ability to collaborate with peers, stakeholders and management

Location Dallas-Fort Worth Metroplex

Description At ServiceLink, we believe in pushing the limits of what’s possible through innovation. We’re looking for a high-achieving AI expert to lead ground-breaking initiatives that redefine our mortgage industry. As our Lead AI Engineer, you’ll harness cutting-edge technologies—from advanced machine learning and deep learning to generative AI, Large Language Models, and Agentic AI—to create production-ready systems that solve real-world challenges. This is your opportunity to shape strategy, mentor top talent, and turn ambitious ideas into transformative solutions in an environment that champions bold thinking and continuous innovation.

Applicants must be currently authorized to work in the United States on a full-time basis and must not require sponsorship for employment visa status now or in the future.

A DAY IN THE LIFE In this role, you will… - Transform complex business challenges into innovative AI solutions that leverage deep learning, LLMs, and autonomous Agentic AI frameworks. - Lead projects end-to-end—from ideation and data gathering to model design, fine-tuning, deployment, and continuous improvement using full MLOps practices. - Collaborate closely with business stakeholders, Data Engineering, Product, and Infrastructure teams to ensure our AI solutions are powerful, secure, and scalable. - Drive both research and production by designing experiments, publishing state-of-the-art work in high-impact journals, and protecting strategic intellectual property. - Mentor and inspire our next generation of Data scientists and AI Engineers, sharing insights on emerging trends and best practices in AI.

WHO YOU ARE You possess … - A visionary leader with an advanced degree (Master’s or Ph.D.) in Computer Science, Engineering, or a related field, backed by 7+ years of progressive experience in AI and data science. - A technical powerhouse with a solid track record in statistical analysis, machine learning, deep learning, and building production-grade models using transformer architectures and Agentic AI systems. - Re-engineered conventional workflows leveraging AI technologies, achieving measurable business outcomes. - Proficient in Python—and comfortable with other modern programming environments—armed with real-world experience in cloud platforms (preferably Microsoft Azure) and end-to-end AI development (CRISP-DM and ML-Ops). - An exceptional communicator who can distill complex technical ideas into strategic insights for diverse audiences, from the boardroom to the lab. - A proactive problem solver and collaborative team player who thrives in a fast-paced, interdisciplinary setting, ready to balance innovative risk with practical execution.

Global - United States, Europe, Asia

Quantitative Researchers play a key role in this mission by developing next-generation models and trading approaches for a range of investment strategies. You’ll get to challenge the impossible in quantitative research by applying sophisticated and complex statistical techniques to financial markets, some of the most complex data sets in the world.

The Department of Materials Science and Engineering (DMSE) together with the Schwarzman College of Computing (SCC) at Massachusetts Institute of Technology (MIT) in Cambridge, MA, seeks candidates at the level of tenure-track Assistant Professor to begin July 1, 2026 or on a mutually agreed date thereafter.

Materials engineering has always benefitted from theoretical and computational approaches to unveil relationships between structure, properties, processing, and performance. Recent advances in computing, including but not limited to artificial intelligence, are poised to dramatically advance the understanding and design of complex matter. DMSE and SCC jointly seek candidates with experience and interest in combining fundamental scientific principles with algorithmic innovations to empower discovery, understanding, and synthesis of materials with applications across critical societal domains --- healthcare, manufacturing, energy, sustainability, climate, and next-generation computing. This search encompasses all materials classes and scales, and is open to candidates with industry and start-up experience. Candidates are expected to develop research programs that target innovation in computational approaches well-suited to materials science and engineering research.

The successful candidate will have a shared appointment in both the Department of Materials Science and Engineering and SCC in either the Department of Electrical Engineering and Computer Science (EECS) or the Institute for Data, Systems, and Society (IDSS), depending on best fit.

Faculty duties include teaching at the undergraduate and graduate levels, advising students, conducting original scholarly research, and developing course materials at the graduate and undergraduate levels. Candidates are expected to teach in both the Department of Materials Science and Engineering and in the educational programs of SCC. The normal teaching load is two subjects per year.

Candidates should hold a Ph.D. in Materials Science and Engineering, Computer Science, Physics, Chemical Engineering, Chemistry, Applied Mathematics, or a related field. A PhD is required by the start of employment. The pay range for a 9-month academic appointment at the entry-level Assistant Professor rank (excluding summer salary): $140,000 - $150,000. The pay offered to a selected candidate during hiring will be based on factors such as (but not limited to) the scope and responsibilities of the position, the individual's work experience and education/training, internal peer equity, and applicable legal requirements. These factors impact where an individual's pay falls within a range. Employment is contingent upon the completion of a satisfactory background check, including verifying any finding of misconduct (or pending investigation) from prior employers.

Applications should include: (a) curriculum vitae, (b) research statement, (c) a teaching and mentoring plan. Each candidate should also include the names and contact information of 3 reference letter writers, who should upload their letters of recommendation by November 30, 2025.

Please submit online applications to https://faculty-searches.mit.edu/dmse_scc/register.tcl. To receive full consideration, completed applications must be submitted by November 30, 2025.

MIT is an equal opportunity employer. We value diversity and strongly encourage applications from individuals from all identities and backgrounds. All qualified applicants will receive equitable consideration for employment based on their experience and qualifications and will not be discriminated against on the basis of race, color, sex, sexual orientation, gender identity, pregnancy, religion, disability, age, genetic information, veteran status, or national or ethnic origin. See MIT's full policy on nondiscrimination. Know your rights.

Location Beijing CHINA

Description

1. Role and Value： BAAI is seeking Principal Investigators to act as our scientific leaders and team builders. We will grant you significant resources and trust, empowering you to build high-performing R&D teams from the ground up and lead the charge in solving research and engineering challenges of world-class significance.

2. Qualifications：

3. A proven track record of successfully establishing, leading, and motivating high-caliber R&D teams, demonstrating exceptional leadership.
4. Outstanding talent-spotting abilities, with expertise in attracting, nurturing, and mentoring young talent to form globally competitive research groups.
5. Extensive experience in managing and delivering major national or enterprise-level R&D projects with a record of outstanding outcomes.

6. A strong publication record in premier academic conferences/journals and/or a portfolio of high-value patents.

7. We Offer：

8. Industry-leading compensation with substantial performance-based bonuses linked to project milestones.
9. Substantial autonomous project funding and access to state-of-the-art computing resources.
10. Priority access to subsidized talent apartments and comprehensive support for Beijing residency registration.
11. An open research environment and extensive industry collaboration network to help translate innovative ideas into real-world impact.

12. Comprehensive commercial health insurance for you and your family.

13. How to Apply： Please send your CV, a summary of key project experiences, and a list of representative achievements (papers/patents) to: [recruiting@baai.ac.cn] Use the email subject line: "Principal Investigator Application - [Name] - [Research Focus]"

Bala Cynwyd (Philadelphia Area), Pennsylvania United States

Overview At Susquehanna, we approach quantitative finance with a deep commitment to scientific rigor and innovation. Our research leverages vast and diverse datasets, applying cutting-edge machine learning at scale to uncover actionable insights—driving data-informed decisions from predictive modeling to strategic execution.

We are launching a 12–18 month fully funded faculty fellowship. This is a unique opportunity to pursue advanced machine learning research in a fast-paced, real-world environment—collaborating with teams at the frontier of quantitative trading.

What You'll Do

 • Conduct applied machine learning research using large-scale, real-world financial datasets

 • Develop novel modeling techniques and adapt state-of-the-art algorithms to unique challenges in quantitative finance

 • Collaborate with researchers and engineers to translate theoretical insights into production-scale systems.

 • Contribute to the design of robust, high-performance ML infrastructure

 • Explore research directions aligned with your interests, with flexibility in scope and duration

 • Evaluate ideas in an industrial setting, generating insights that may inform future academic or applied work

 • Help grow our research community by fostering collaboration and leveraging your network within the ML and academic ecosystems

What we're looking for • Exceptional faculty (tenured or tenure-track) with expertise in machine learning, deep learning, LLM, statistics, computer science, physics, applied mathematics, or related fields

 • Exceptional newly minted PhDs or postdocs developing a research agenda in machine learning, deep learning, LLM,  statistics, computer science, physics, applied mathematics, or related fields

 • A strong theoretical foundation in ML and a passion for solving practical, open-ended problems

 • Strong programming skills (Python preferred); experience with ML frameworks like PyTorch, TensorFlow or Jax

 • Intellectual curiosity, adaptability, and a collaborative mindset

Note: This fellowship is ideal for faculty seeking to broaden their applied research portfolio, explore new domains, or engage in sabbatical collaborations. The faculty fellowship is also appropriate for exceptional newly minted PhD and postdocs who want to develop a research agenda (involving, but not limited to, modeling, inference, and prediction tasks in complex systems), as they prepare to transition into a faculty position. While research outputs cannot be published due to the proprietary nature of our work, we aim for each faculty fellow to publish technical research papers collaboratively with their research hosts, to showcase some of the machine learning and AI innovations that they developed while in residence at Susquehanna.

USA - Austin, Seattle

Job Overview

At Arm, we’re redefining what’s possible with AI. Whether it’s enabling edge devices to see and hear, empowering cloud platforms to learn at scale, or pioneering energy-efficient compute for autonomous systems - our AI engineers are at the forefront of building a smarter, connected world.

We’re looking for AI Engineers who are excited by the challenges and opportunities AI presents across industries. From optimizing machine learning performance on next-gen processors to contributing to cutting-edge research, if you’re passionate about the future of AI, we want to meet you.

Responsibilities

Depending on your background and experience, you could be involved in:

Designing and optimizing machine learning models for efficient deployment on Arm-based platforms Building high-performance AI software tools, libraries, and compilers Leading system-level architecture for next-gen AI accelerators Partnering with ecosystem collaborators on real-world ML applications Pushing the boundaries of AI/ML research for embedded, edge, or cloud use cases Understanding and working in a deep technology stack to deliver intelligent, efficient compute

Required Skills and Experience

Strong programming skills in Python, C/C++, or similar languages used in AI and high-performance computing Hands-on experience with machine learning frameworks such as TensorFlow, Pytorch, or ONNX Deep technical understanding of AI/ML model development, training, and inference Experience leading the design and architecture of reliable and scalable systems Ability to work across disciplines in a collaborative, technically ambitious, and fast-paced environment Excellent communication skills and problem solving mindset

“Nice to Have” Skills and Experience

Experience in model optimization for performance, efficiency, or deployment Exposure to deploying machine learning models on edge, devices, or mobile platforms Familiarity with Arm architecture and performance analysis tools

San Francisco, CA, US; Palo Alto, CA, US; Seattle, WA, US; Remote, US

About Pinterest:

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.

At Pinterest Labs, you'll join a world-class team of research scientists and machine learning engineers to tackle cutting-edge challenges in machine learning and artificial intelligence. This role places you at the intersection of applied research and scalable infrastructure, focusing heavily on ML framework and efficiency.

You will conduct research that can be applied across Pinterest engineering teams, engaging in external collaborations and mentoring. Your research focus will specifically target ML efficiency and large-scale infrastructure challenges within high-impact areas such as: generative recommender systems, post-training, reinforcement learning, multi-modality representation learning, and graph neural networks.

What you’ll do:

• Design, develop, maintain, and enhance advanced machine learning solutions across various key business areas.
• Lead the technical strategy for optimizing and improving the efficiency of large-scale ML infrastructure.
• Lead high-impact machine learning projects, overseeing priorities, deadlines, and deliverables while providing technical guidance.
• Drive alignment and clarity on goals, outcomes, and timelines across teams.

What we’re looking for:

• MS/PhD in Computer Science or a related field degree.
• 10+ years of industry experience.
• Experience in distributed systems, ML frameworks (e.g. PyTorch), and scaling laws.
• Experience in research and in solving analytical problems.
• Cross-functional collaborator and strong communicator.
• Comfortable solving ambiguous problems and adapting to a dynamic environment.