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

Boston/NYC/LA/SF

About Suno

At Suno, we are building a future where anyone can make music. You can make a song for any moment with just a few short words. Award-winning artists use Suno, but our core user base consists of everyday people making music — often for the first time.

We are a team of musicians and AI experts, including alumni from Spotify, TikTok, Meta and Kensho. We like to ship code, make music and drink coffee. Our company culture celebrates music and experimenting with sound — from lunchroom conversations to the studio in our office.

Over the last two years, nearly 100 million people have made music on Suno – many for the first time in their lives, discovering a passion they never knew they had. And this isn’t just a story about new creators: top producers and songwriters have integrated Suno into their daily workflows, and new artists emerging on Suno are being recognized by the industry’s most important charts. Suno has become a platform where imagination meets reality, at every level of the creative journey.

Recently Suno announced its 250M Series C at a 2.45B post-money valuation.

About the Role

We’re looking for research scientists and engineers to build foundation models for music and audio. Our research focuses not only on generative tasks, but also understanding such as source separation, captioning, lyrics transcription, midi transcription, and alignment.We have roles open for pre-training, post-training, multimodal architectures, data, distributed training, and inference optimization. We are a small research team with a very large cluster, serving millions of users daily.

Healthcare for you and your dependents, with vision and dental

401k with match

Generous commuter benefit

Flexible PTO

San Jose, CA, USA

We are seeking a creative and technically skilled Prompt Engineer to enhance large language model (LLM) performance across business-critical workflows. This position centers on designing, testing, and integrating strategies that drive intelligent agents and enterprise use cases. You will work closely with AI engineers, product teams, and domain experts to guarantee scalable, safe, and high-accuracy AI applications.

What you'll Do - Prompt Strategy & Design: Develop templates and multi-step chains tailored to specific business functions (e.g., sales enablement, support, knowledge management). Develop few-shot, zero-shot, and hybrid patterns for enhanced reasoning and context retention. Maintain libraries for reuse and version control.

• Function Calling & Tool Use: Implement LLM function calling to trigger APIs, databases, or internal tools. Build tool-use pipelines within agent workflows for complex task automation.

• Conversation Flow & Persona Design: Define and build agent personas, roles, and behaviors for domain-specific applications. Manage multi-turn conversations, memory handling, and contextual continuity.

• Enterprise-grade Optimization: Tailor prompts for performance in enterprise environments, prioritizing accuracy, privacy, fairness, and compliance. Collaborate with legal and security teams to mitigate hallucination, bias, and misuse risks.

• Testing & Evaluation: Tailor prompts for performance in enterprise environments, prioritizing accuracy, privacy, fairness, and compliance. Collaborate with legal and security teams to mitigate hallucination, bias, and misuse risks.

• Deployment & Integration: Partner with AI Agent Engineers to integrate prompts into agent workflows and orchestration pipelines. Maintain documentation and workflows for deployment in production environments.

What you need to succeed - 3+ years of experience in NLP, AI/ML product development, or application scripting - Strong grasp of LLM capabilities and limitations (e.g., OpenAI, Claude, Mistral, Cohere) - Experience crafting prompts and evaluation methods for enterprise tasks - Familiarity with frameworks like LangChain, Semantic Kernel, or AutoGen - Strong Python and API integration skills - Excellent written communication and structured thinking

Preferred Qualifications - Experience with LLM function calling, custom tool integration, and agent workflows - Background in UX writing, human-computer interaction, or instructional design - Understanding of enterprise compliance (e.g., SOC 2, GDPR) in AI systems - Bachelor's or equivalent experience in Computer Science, Computational Linguistics, Cognitive Science, or a related field

The role We are seeking a highly skilled and customer-focused professional to join our team as a Cloud Solutions Architect specializing in Cloud infrastructure and MLOps. As a Cloud Solutions Architect, you will play a pivotal role in designing and implementing cutting-edge solutions for our clients, leveraging cloud technologies for ML/AI teams and becoming a trusted technical advisor for building their pipelines.

You’re welcome to work remotely from the US or Canada.

Your responsibilities will include: - Act as a trusted advisor to our clients, providing technical expertise and guidance throughout the engagement. Conduct PoC, workshops, presentations, and training sessions to educate clients on GPU cloud technologies and best practices. - Collaborate with clients to understand their business requirements and develop solution architecture that align with their needs: design and document Infrastructure as code solutions, documentation and technical how-tos in collaboration with support engineers and technical writers. - Help customers to optimize pipeline performance and scalability to ensure efficient utilization of cloud resources and services powered by Nebius AI. - Act as a single point of expertise of customer scenarios for product, technical support, marketing teams. - Assist to Marketing department efforts during events (Hackathons, conferences, workshops, webinars, etc.)

We expect you to have: - 5 - 10 + years of experience as a cloud solutions architect, system/network engineer, developer or a similar technical role with a focus on cloud computing - Strong hands-on experience with IaC and configuration management tools (preferably Terraform/Ansible), Kubernetes, skills of writing code in Python - Solid understanding of GPU computing practices for ML training and inference workloads, GPU software stack components, including drivers, libraries (e.g. CUDA, OpenCL) - Excellent communication skills - Customer-centric mindset

It will be an added bonus if you have: - Hands-on experience with HPC/ML orchestration frameworks (e.g. Slurm, Kubeflow) - Hands-on experience with deep learning frameworks (e.g. TensorFlow, PyTorch) - Solid understanding of cloud ML tools landscape from industry leaders (NVIDIA, AWS, Azure, Google)

About the multiple postdoctoral fellowship positions: Join the Deep Learning for Precision Health Lab at the University of Texas Southwestern to build next-generation AI for medicine with direct access to large, deeply-phenotyped datasets and clinical partners across UT Southwestern Medical Center, Children’s Medical Center, and Parkland Hospital. Roles are ideal for researchers who have recently (or will soon) completed a PhD (typically ≤3 years from degree). Based in Dallas—one of the largest, most vibrant, and fastest-growing cities in the U.S. —fellows work closely with Prof. Albert Montillo, PhD (Associate Professor, tenured, Fellow of IEEE/ MICCAI / ISMRM / OHBM / SPIE/ ASNR) and collaborate with neurologists, radiologists, psychiatrists, and neuroscientists on clinically grounded problems—aimed at high-impact publications and deployable methods.

Project tracks (pick one or blend across): 1. Deep multimodal fusion models & GNNs: Integrate multi-contrast MRI & PET with electrophysiology, EHR/clinical data, and multi-omics via deep fusion and graph learning to predict disease trajectories and treatment response (Opportunities in Parkinson’s, AD, ASD, epilepsy, depression). 2. Image foundation models (FMs): Pretrain & fine-tune on very large medical image datasets (10k–100k+ subjects) for site-generalizable transfer to downstream tasks with per-subject explainability. 3. Bayesian Causal Discovery method development: Combine neuroimaging, interventional data, and priors to infer effective brain connectivity and mechanisms in developmental disorders (epilepsy, ASD).
4. Reinforcement learning to guide neuromodulation therapy: Fuse computational neuroscience models with data-driven FMs, optimizing neuromodulation under uncertainty. 5. Speech + Imaging for early dementia: Build multimodal FMs over voice (audio), language (linguistics/NLP), and neuroimaging for earliest, most accurate dementia diagnosis.

Required Qualifications:

1. We will only consider scholars having (or will have) PhD degrees in CS, ECE, Applied Math, Computational Physics, BME, Bioinformatics, Statistics, or related field with machine learning and signal/audio/text or omics analysis experience (e.g., MRI/CT/PET; MEG/EEG; speech/voice; NLP/clinical text; genomics/proteomics).
2. Proficient in DL programming in Python (PyTorch/TensorFlow) and strong mathematical training for fast DL prototyping.
3. Major contributions in peer-reviewed publications at top venues: NeurIPS/ICLR/ICML/AAAI, MICCAI, CVPR/ICCV, journals such as TPAMI, TMI, MedIA, Nature Communications, and related high-impact outlets.

Appointment and support:

Full-time position with competitive salary & benefits, based in Dallas, TX, USA. Initial appointment is 1 year, renewable; fellows should plan for minimum 2-yr commitment. US citizens strongly encouraged; visa sponsorship for exceptional international candidates. Start window: early 2026; later starts considered.

For consideration:

Reach out for an in-person meeting in San Diego at NeurIPS 2025 (or virtually afterwards) via email to Albert.Montillo@UTSouthwestern.edu with the subject “Postdoc-Applicant-MM/FM-NeurIPS” and include: (1) CV, (2) contact info for 3 references, (3) up to 3 representative publications, and (4) your preferred track(s) + start window. Positions open until filled; review begins immediately.

Location: Aalto University, Finland

Topic: Generative Models, Geometric Deep Learning, Neurosymbolic Methods

Applications: LLMs and Drug Discovery

Ideal background: Strong mathematical/theoretical training, and experience and comfort with programming in deep learning

Contact: Send an email with your CV to Vikas Garg (vgarg@csail.mit.edu)
​​​

AI Engineer - Agentic AI for scientific workflows

Location: Boston (US) / Barcelona (Spain)

Position overview:

As an AI Engineer specialized in Agentic AI workflows, you will play a key role in building new verifiable workflows for science and engineering. Your responsibilities will include designing, prototyping, developing and testing our pipeline. You will also manage data curation, conduct benchmarking to evaluate performance, analyze reasoning flaws and propose solutions. Close collaboration with our dedicated cross-functional team - consisting of AI Engineers, Software Engineers, Physicists and AI scientists - will be essential to the success of the project.

Your mission:

• AI Development: Contribute to the development of novel AI reasoning models and architectures, focusing on advanced reasoning techniques and application to scientific fields where rigour and reliability are fundamental.
• Data & Benchmarking: Supervise dataset curation, run benchmarks, and analyze performance results to guide improvements.
• Collaboration: Work closely with a cross-functional team of engineers and scientists, collaborating on solving challenging problems at the intersection of AI, physics and engineering.
• Documentation and Reporting: Develop detailed technical documentation and present research findings to internal teams and external stakeholders.
• Research & Publication: Contribute to cutting-edge research and publish results in top AI conferences and journals, helping advance the global AI research community whenever opportunities arise.

Key requirements:

• Master’s degree in Data Science, Computer Science, Information Technology, Artificial Intelligence, Physics or related field.
• 2+ years of experience, preferably in a mathematical, engineering, scientific, or technical setting.
• At least one year of experience in agentic AI applications
• Strong communication skills
• Ability to collaborate effectively within a multidisciplinary and multicultural environment
• Curiosity, and a proactive, solution-oriented mindset
• Excitement to work in a dynamic and fast-paced environment, thrives in ambiguity
• Personal interest in exploring most recent AI developments and keeping up to state of the art

Technical skills:

• Proficiency in Python
• Understanding of fundamental computer science principles
• Proficiency in agentic and deep learning frameworks
• Solid understanding of machine learning principles and architectures
• Fundamentals of statistics
• Hands-on experience with large language models
• Excellent research and analytical skills

Preferred Qualifications (Nice to Have):

• Proven excellence in relevant areas (e.g., awards, competition wins)
• Demonstrated curiosity and passion for AI (e.g., personal projects, outreach activities, hobby work) or proven contributions to open-source projects
• Proven ability to independently solve complex problems or lead challenging projects
• Academic or practical background in physics or other natural sciences
• Experience with good coding practices and software development standards
• Familiarity with recent AI pipelines and protocols e.g. MCP tools/servers

The role We seek an experienced AI/ML Specialist Solutions Architect to support AI-focused customers leveraging Nebius services. In this role, you will be a trusted advisor, collaborating with clients to design scalable AI solutions, resolve technical challenges and manage large-scale AI deployments involving hundreds to thousands of GPUs.

You’re welcome to work remotely from the United States or Canada.

Your responsibilities will include: - Designing customer-centric solutions that maximize business value and align with strategic goals. - Building and maintaining long-term relationships to foster trust and ensure customer satisfaction. - Delivering technical presentations, producing whitepapers, creating manuals and hosting webinars for audiences with varying technical expertise. - Collaborating with engineering and product teams to effectively prioritize and relay customer feedback.

We expect you to have: - 7-10 + years of experience with cloud technologies in MLOps engineering, Machine Learning engineering or similar roles. - Strong understanding of ML ecosystems, including models, use cases and tooling. - Proven experience in setting up and optimizing distributed training pipelines across multi-node and multi-GPU environments. - Hands-on knowledge of frameworks like PyTorch or JAX. - Excellent verbal and written communication skills.

It will be an added bonus if you have: - Expertise in deploying inference infrastructure for production workloads. - Ability to transition ML pipelines from POC to scalable production systems.

Preferred tooling: - Programming Languages – Python, Go, Java, C++ - Orchestration – Kubernetes (K8s), Slurm - DevOps Tools – Git, Docker, Helm - Infrastructure as Code (IaC) – Terraform - ML Frameworks and Libraries – PyTorch, TensorFlow, JAX, HuggingFace, Scikit-learn

London

Flow Traders is committed to leveraging the most recent advances in machine learning, computer science, and AI to generate value in the financial markets. We are looking for Quantitative Researchers to join this challenge.

As a Quantitative Researcher at Flow Traders, you are an expert in mathematics and statistics. You are passionate about translating challenging problems into equations and models, and have the ability to optimize them using cutting-edge computational techniques. You collaborate with a global team of researchers and engineers to design, build, and optimize our next generation of models and trading strategies.

Are you at the top of your quantitative, modeling, and coding game, and excited by the prospect of demonstrating these skills in competitive live markets? Then this opportunity is for you.

Location: Perth, Australia

Research Associate

Job Reference: 521359
Employment Type: Full Time (Fixed Term, 2 Years)
Categories: Arts, Business, Education, Law

Remuneration

Base salary: Level A, $83,499–$112,371 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 design, test, and refine computer vision models for traffic video analytics, including detection, tracking, segmentation, and post-processing tasks. You will prepare and manage datasets, benchmark emerging frameworks, and contribute to deployment testing and optimisation across varied environments. Working within a small team, you will document findings, produce technical outputs, and contribute to research that influences road safety and transport planning.

Selection Criteria

Essential:

• Tertiary degree in Computer Science, Applied Mathematics/Statistics, Robotics, Physics or related discipline, with excellent academic record
• Strong foundations in applied mathematics, computer vision and machine learning, particularly object detection and tracking
• Proficiency in deep learning frameworks (e.g., PyTorch, TensorFlow) and Python ML libraries (e.g., NumPy, OpenCV, scikit-learn)
• Experience with dataset preparation, training pipelines, and evaluation methods
• Ability to work independently and collaboratively in a research team

Further Information

Position Description: PD [Research Associate] [521359].pdf

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