Various locations available

Adobe seeks a Machine Learning Engineer to enhance customer experiences through AI and generative technologies. This is an exciting internship opportunity inside Adobe Firefly’s applied research organization. You will be surrounded by amazing talents who build the Firefly family of models from research inception all the way to production. We offer internship roles situated at different stages of the development pipeline from fundamental research to advanced development to production engineering directly shaping the training and integration of Firefly production models. Your role will center on pioneering data, models, applications and scientific evaluation that shape the future of technology in the realms of images, videos, language and multimodal models. Join us in reshaping the future of technology and customer experiences at Adobe!

What You’ll Do

• Work towards results-oriented research goals, while identifying intermediate achievements.
• Contribute to research and advanced development that can be applied to Adobe product development.
• Help integrating novel research work into Adobe Firefly product.
• Lead and collaborate on projects across different teams.

What You Need to Succeed

• Currently enrolled full time and pursuing a Master's or PhD in Computer Science, Computer Engineering, Electrical Engineer or related fields.
• 1 + years of experience in computer vision, natural language processing or machine learning
• Some experience in Generative AI
• Experience communicating research to public audiences of peers.
• Experience working in teams.
• Knowledge in Python and typical machine learning development toolkits.
• Ability to participate in a full-time internship between May-September.

ABOUT THE ROLE

You will be focused on building out our multi-device inference of Large Language Models, both standard transformers and custom linear attention architectures. You will be working with lowered precision inference and tensor parallelism. You will be comfortable diving into vLLM, Torch, AWS libraries. You will be working on improvements for both NVIDIA and AWS hardware. You will be working on the bleeding edge of what's possible and will find yourself, hacking and testing the latest vendor solutions. We are rewrite-in-Rust-friendly.

YOUR MISSION

To develop and continuously improve the inference of LLMs for source code generation, optimizing for the lowest latency, the highest throughput, and the best hardware utilization.

RESPONSIBILITIES

• Follow the latest research on LLMs, inference and source code generation
• Propose and evaluate innovations, both in the quality and the efficiency of the inference
• Monitor and implement LLM inference metrics in production
• Write high-quality high-performance Python, Cython, C/C++, Triton, ThunderKittens, native CUDA, Amazon Neuron code
• Work in the team: plan future steps, discuss, and always stay in touch

SKILLS & EXPERIENCE

• Experience with Large Language Models (LLM)
• Confident knowledge of the computational properties of transformers
• Knowledge/Experience with cutting-edge inference tricks
• Knowledge/Experience of distributed and lower precision inference
• Knowledge of deep learning fundamentals
• Strong engineering background
• Theoretical computer science knowledge is a must
• Experience with programming for hardware accelerators
• SIMD algorithms
• Expert in matrix multiplication bottlenecks
• Know hardware operation latencies by heart
• Nice to have but not required: Author of scientific papers on any of the topics: applied deep learning, LLMs, source code generation, etc
• Can freely discuss the latest papers and descend to fine details
• Programming experience: Linux, Git, Python with PyTorch or Jax, C/C++, CUDA, Triton, ThunderKittens
• Use modern tools and are always looking to improve
• Opinionated but reasonable, practical, and not afraid to ignore best practices
• Strong critical thinking and ability to question code quality policies when applicable
• Prior experience in non-ML programming is a nice to have

PROCESS

• Intro call with one of our Founding Engineers
• Technical Interview(s) with one of our Founding Engineers
• Team fit call with the People team
• Final interview with one of our Founding Engineers

BENEFITS

• Fully remote work & flexible hours
• 37 days/year of vacation & holidays
• Health insurance allowance for you and dependents
• Company-provided equipment
• Wellbeing, always-be-learning and home office allowances
• Frequent team get togethers
• Great diverse & inclusive people-first culture

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.

Rochester, Minnesota, USA

Mayo Clinic seeks a highly motivated individual to advance the development, validation, and real-world implementation of generative AI systems for clinical decision support in Gastroenterology and Hepatology. This role bridges research and translation into clinical workflows, focusing on building trustworthy AI systems that augment human presence and put the needs of the patient first. Research Fellows will work within a multidisciplinary team of data scientists, physicians, and engineers to design novel generative agentic architectures, develop useful benchmarks, and work together with clinical teams to decrease time to diagnosis and time to treatment. Contact shung.dennis@mayo.edu if interested.

New York

Quantitative Researchers (QRs) specialize in a variety of areas, including but not limited to: using sophisticated data analysis skills to build predictive models, driving construction of a complex multi asset portfolio by utilizing large scale portfolio optimization techniques, and developing sophisticated optimization algorithms. Researchers with an exceptional record of achievement in their respective fields and a drive to apply quantitative techniques to investing are encouraged to apply to GQS.

Location United States

Description At Oracle Cloud Infrastructure (OCI), we are building the future of cloud computing—designed for enterprises, engineered for performance, and optimized for AI at scale. We are a fast-paced, mission-driven team within one of the world’s largest cloud platforms. The Multimodal AI team in OCI Applied Science is working on developing cutting-edge AI solutions using Oracle's industry leading GPU-based AI clusters to disrupt industry verticals and push the state-of-the-art in Multimodal and Video GenAI research. You will work with a team of world-class scientists in exploring new frontiers of Generative AI and collaborate with cross-functional teams including software engineers and product managers to deploy these globally for real-world enterprise use-cases at the largest scale.

Responsibilities: - Contribute to the development and optimization of distributed multi-node training infrastructure - Stay Updated: Maintain a deep understanding of industry trends and advancements in video generatio, multimodal understanding, pretraining workflows and paradigms. -Model Development: Design, develop, and train state-of-the-art image and vide generation models that meet the highest quality standards. - Collaborate with cross-functional teams to support scalable and secure deployment pipelines. - Assist in diagnosing and resolving production issues, improving observability and reliability. - Write maintainable, well-tested code and contribute to documentation and design discussions

Minimum Qualifications - BS in Computer Science or related technical field. - 6+ years of experience in backend software development with cloud infrastructure. - Strong proficiency in at least one language such as Go, Java, Python, or C++. - Experience building and maintaining distributed services in a production environment. - Familiarity with Kubernetes, container orchestration, and CI/CD practices. - Solid understanding of computer science fundamentals such as algorithms, operating systems, and networking.

Preferred Qualifications - MS in Computer Science. - Experience in large-scale multi-node distributed training of LLMs and multimodal models. - Knowledge of cloud-native observability tools and scalable service design. - Interest in compiler or systems-level software design is a plus.

Why Join Us - Build mission-critical AI infrastructure with real-world impact. - Work closely with a collaborative and experienced global team. - Expand your knowledge in AI, cloud computing, and distributed systems. - Contribute to one of Oracle’s most innovative and fast-growing initiatives.

Disclaimer:

Certain US customer or client-facing roles may be required to comply with applicable requirements, such as immunization and occupational health mandates.

Range and benefit information provided in this posting are specific to the stated locations only

US: Hiring Range in USD from: $96,800 to $223,400 per annum. May be eligible for bonus and equity.

Oracle maintains broad salary ranges for its roles in order to account for variations in knowledge, skills, experience, market conditions and locations, as well as reflect Oracle’s differing products, industries and lines of business. Candidates are typically placed into the range based on the preceding factors as well as internal peer equity.

Oracle US offers a comprehensive benefits package which includes the following: 1. Medical, dental, and vision insurance, including expert medical opinion 2. Short term disability and long term disability 3. Life insurance and AD&D 4. Supplemental life insurance (Employee/Spouse/Child) 5. Health care and dependent care Flexible Spending Accounts 6. Pre-tax commuter and parking benefits 7. 401(k) Savings and Investment Plan with company match 8. Paid time off: Flexible Vacation is provided to all eligible employees assigned to a salaried (non-overtime eligible) position. Accrued Vacation is provided to all other employees

San Jose, CA, USA

We are looking for a hands-on, systems-oriented AI Agent Engineer to design, build, and maintain intelligent agents that drive automation and business impact across the enterprise. This role is responsible for the full lifecycle of agent development — from design to versioning, orchestration, and continuous learning.

You’ll contribute directly to scaling our AI strategy by engineering reusable components, optimizing agent workflows, and ensuring real-world performance in production environments.

What you'll Do

• Agent Development: Build and fine-tune specialized AI agents for targeted customer experience use cases such as discovery, support, and lead qualification. Implement prompt engineering strategies, memory handling, resource management and tool-calling integrations

• Multi-Agent Communication: Adopt agent-to-agent communication protocols and handoff mechanisms to enable cooperative task execution and delegation. Build orchestrated workflows across agents using frameworks like LangChain, AutoGen, or Semantic Kernel

• Templates & Reusability: Create reusable agent templates and modular components to accelerate deployment across business units. Build plug-and-play configurations for domain-specific requirements.

• Lifecycle Management & Monitoring: Track and improve conversation quality, task success rate, user satisfaction, and performance metrics. Automate monitoring of agent behavior using observability tools (e.g., Arize, LangSmith, custom dashboards)

• Continuous Improvement: Implement learning workflows, including human-in-the-loop feedback and automatic retraining. Refine prompts and model behavior through structured experimentation and feedback loops.

• Maintenance & Governance: Handle knowledge base updates, drift detection, performance degradation, and integration of new business logic. Ensure agents stay aligned with evolving enterprise data sources and compliance requirements

• Deployment: Manage agent versioning, testing pipelines (unit, regression, UX), and controlled rollout processes. Collaborate with DevOps, QA, and infrastructure teams to ensure scalable deployments

What you need to succeed - 3–5+ years of experience in AI/ML engineering, NLP systems, or backend development - Strong proficiency with LLM frameworks (e.g., OpenAI APIs, LangChain, RAG pipelines) - Experience building conversational agents or workflow bots in production environments - Familiarity with cloud platforms (AWS/GCP/Azure), REST APIs, Python, and containerization (Docker, K8s) - Comfort with prompt design, vector databases, and memory handling strategies

Preferred Qualifications - Experience with multi-agent frameworks or agent orchestration systems - Familiarity with observability tools, data labeling workflows, or synthetic data generation - Background in conversational design or dialogue management systems - Degree in Computer Science, Data Science, Engineering, or a related field

Research Fellow

Job Reference: 521360
Employment Type: Full Time (Fixed Term, 2 Years)
Location: Perth, Western Australia

Remuneration

Base salary: Level B, $118,150–$139,812 p.a. (pro-rata) plus 17% superannuation

The Research Centre

The Planning and Transport Research Centre (PATREC) at UWA conducts research with direct application to transport planning and road safety. RoadSense Analytics (RSA) is a video analytics platform for traffic analysis, developed through seven years of sustained R&D. The platform translates Australian research into a market-ready product for transport planning applications.

The Role

You will lead research and development of advanced computer vision models, multi-object tracking, and post-processing methods to improve traffic video analytics in complex environments. You will drive benchmarking, evaluation, and deployment optimisation of AI models, ensuring scalability and real-world performance. You will publish research, mentor junior staff, and collaborate with engineers and partners to translate innovations into production-ready solutions.

Selection Criteria

Essential:

• Tertiary degree in Computer Science, Applied Mathematics/Statistics, Robotics, Physics, or related discipline, with excellent academic record
• Demonstrated expertise in computer vision and machine learning, including object detection, segmentation, and multi-object tracking in challenging conditions such as occlusions, crowded scenes, and object re-identification
• Proficiency in deep learning frameworks (e.g., PyTorch, TensorFlow) and Python ML libraries (e.g., NumPy, OpenCV, scikit-learn)
• Experience implementing and evaluating state-of-the-art tracking algorithms such as DeepSORT, ByteTrack, and Transformer-based approaches
• Proven ability to design and run rigorous experimental frameworks, including benchmarking, ablation studies, and field validation

Further Information

Position Description: PD [Research Fellow] [521360].pdf

Contact: Associate Professor Chao Sun
Email: chao.sun@uwa.edu.au

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]"

Global

Description

Qualcomm is proud to be attending NeurIPS 2025 in our home city San Diego, California! Qualcomm is powering efficient AI from edge to cloud, conducting novel foundational, platform, and applied AI research to enable intelligent computing everywhere.

We're inviting all those who have a passion for AI and are interested in opportunities in generative AI, visual AI, computer vision, and foundational machine learning to please follow the steps below.

1. Please visit the Qualcomm NeurIPS home page by clicking the URL to apply.

2. Register by clicking on the blue link. This allows us to identify your application as someone we met at NeurIPS.

3. Apply to any of the linked positions on our Qualcomm NeurIPS home page. Make sure you REGISTER first before applying. Your resume will stand out.