Location Beijing CHINA

Description

1. Mission and Positioning： The Beijing Academy of Artificial Intelligence (BAAI) invites strategic scientists from the global AI community to join us as a Chief Scientist. In this role, you will chart the future course for the Academy's and the discipline's development, guiding our exploration of the AI frontier and establishing yourself as an academic leader shaping the global AI landscape.

2. Qualifications：

3. A distinguished research background at world-leading universities, national-level research institutions, or corporate R&D labs of global renown.
4. A proven record of publishing a series of highly influential research findings in top-tier AI journals and conferences, with the ability to define the frontiers of the discipline.

5. Visionary strategic insight and exceptional academic leadership, with a demonstrated capacity to identify and tackle the field's most fundamental challenges.

6. We Offer：

7. A globally competitive compensation package and comprehensive benefits (customized arrangements are available).
8. Full academic autonomy supported by substantial, long-term research funding and access to world-class computing infrastructure.
9. Full support to assemble and lead an elite research team from around the world.
10. Expedited Beijing residency registration for eligible candidates and access to a premium medical "Green Channel" for senior talent.

11. Customized supplementary health insurance plans for experts and their immediate family members.

12. How to Apply： Please send your detailed CV, representative publications, and a brief research vision statement to: [recruiting@baai.ac.cn] Use the email subject line: "Chief Scientist Application - [Name] - [Primary Research Field]"

Remote - Americas

Applied Machine Learning Engineer - Search

Every day, millions of people search for products across Shopify's ecosystem. That's not just queries—that's dreams, businesses, and livelihoods riding on whether someone finds the perfect vintage jacket or the exact drill bit they need. As a Machine Learning Engineer specializing in Search Recommendations, you'll be the one making that magic happen. With a search index unifying over a billion products, you're tackling one of the hardest search problems at unprecedented scale. We're building cutting-edge product search from the ground up using the latest LLM advances and vector matching technologies to create search experiences that truly understand what people are looking for.

Key Responsibilities:

• Design and implement AI-powered features to enhance search recommendations and personalization
• Collaborate with data scientists and engineers to productionize data products through rigorous experimentation and metrics analysis
• Build and maintain robust, scalable data pipelines for search and recommendation systems
• Develop comprehensive tools for evaluation and relevance engineering, following high-quality software engineering practices
• Mentor engineers and data scientists while fostering a culture of innovation and technical excellence

Qualifications:

• Expertise in relevance engineering and recommendation systems, with hands-on experience in Elasticsearch, Solr, or vector databases
• Strong proficiency in Python with solid object-oriented programming skills
• Proven ability to write optimized, low-latency code for high-performance systems
• Experience deploying machine learning, NLP, or generative AI products at scale (strong plus)
• Familiarity with statistical methods and exposure to Ruby, Rails, or Rust (advantageous)
• Track record of shipping ML solutions that real users depend on

This role may require on-call work

Ready to connect merchants with their perfect customers? Join the team that's making commerce better for everyone.


At Shopify, we pride ourselves on moving quickly—not just in shipping, but in our hiring process as well. If you're ready to apply, please be prepared to interview with us within the week. Our goal is to complete the entire interview loop within 30 days. You will be expected to complete a live pair programming session, come prepared with your own IDE.


Palo Alto, CA

Position Description: Tesla is building robust embodied intelligence through autonomous driving and humanoid robots. Core to reaching this goal is developing intelligent agents that see, move, and speak in the real world. In this role, you’ll architect and deploy models that allow our agents to listen, understand, and respond in real time powered by our custom AI chip on our embodied products. Your work will be central to making Optimus or our cars as seamless as talking to a friend. Most importantly, you will see your work repeatedly shipped to and utilized by thousands of Humanoid Robots in real world applications and millions of cars.

Responsibilities: Define long-term architectural vision and key milestones for speech-powered, expressive character systems Design and develop low-latency, streaming-friendly neural models that integrate audio, language, and non-verbal cues Implement multimodal models for robust speech-to-speech, emotion recognition, and expressive response generation Drive the character-building lifecycle from research prototypes to polished, production-grade experience Test your models E2E on robotic platforms

Requirements: Strong software engineering practices and is very comfortable with Python and Numpy programming, debugging/profiling, and version control
Experience with speech-related machine learning tasks: ASR, emotion detection, speaker diarization, or multimodal input processing Experience training and fine-tuning large-scale speech models, LLMs, or VLMs
Familiarity with real-time audio processing and latency-constrained systems

ABOUT THE ROLE

You’ll join our Applied Research Engineering group to help build poolside’s coding agents. Your work will center on building the core agent framework, the supporting tools, and the orchestration environment needed to run coding agents securely, reliably, and at scale.

We’re looking for strong software engineers with a passion for building reliable, high-performance systems. Experience (or strong interest) in AI coding agents is a significant plus.

In this role, you’ll collaborate closely with our product engineering and research teams to continuously build and improve our platform for coding agents.

YOUR MISSION

Help us design and deliver the most capable AI agents for software engineering tasks, pushing the boundaries of what AI agents can do.

RESPONSIBILITIES

• Design, build, and maintain the core framework for poolside’s coding agents
• Develop scalable, secure, and isolated environments to run agents in complex enterprise environments
• Collaborate with research and product teams to prototype, develop, and evaluate new agent capabilities
• Continuously improve the performance, reliability, and developer experience of our platform

SKILLS & EXPERIENCE

• Solid understanding of AI agents, or a strong interest in developing expertise in this area
• Strong programming skills in either Go, C, C++ or Python (we are open to polyglot engineers from other languages)
• Plus: Experience in large scale, distributed data systems
• Plus: Familiarity with container runtimes, microVMs, or sandboxing systems

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

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.

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

AI Scientist - Formal methods for science

Position overview:

As an AI Research Scientist with focus on formal methods for science, you will join a focused team, playing a key role in building new formal verification tools for science and engineering. Your responsibilities will include developing AI tools that will enable the systematic adoption of formal methods in quantitative scientific fields such as physics and engineering. 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 Mathematicians, AI Engineers, Software Engineers, Lean4 developers, Physicists and AI scientists - will be essential to the success of the project.

Your mission:

• Project contribution and technical execution: Play an active role in designing and developing autoformalization and validation strategies specifically tailored for scientific applications.

• Solution design & implementation: Engage in hands-on development to drive shorter-term impactful solutions in collaboration with our Business Development team. Propose, discuss, and implement technical solutions that address complex challenges, ensuring they are are well-structured, efficient, and aligned with industry best practices.

• Innovation & continuous learning: Stay updated with state-of-the-art techniques and advancements in the field. Continuously integrate the latest research and technologies to enhance the products’ impact.

• Cross-team collaboration: Work closely with AI and development teams to ensure seamless integration of solutions. Promote open communication and cooperation to enhance productivity and technical excellence.

• Knowledge sharing and developing the team: Foster a collaborative culture by actively sharing knowledge, insights, and best practices. Encourage teamwork and continuous learning to strengthen overall expertise within the company.

Key requirements:

• PhD in Computer Science, Artificial Intelligence, Physics, Machine Learning for scientific applications or related fields.
• Experience in applications of machine learning to relevant projects
• Proficient in Python, with the ability to write clean and efficient code
• Experienced with agentic AI and major deep learning framework
• Solid understanding of statistics and probability

About you:

• You excel as a team player, thriving in multidisciplinary and multicultural environments.
• You are highly motivated, hard-working, and committed to personal and professional growth through constant learning, new challenges and advancements.
• You quickly grasp new concepts and technologies, adapting efficiently to evolving requirements.
• You have a real passion for science and maths, and have a deep curiosity for understanding concepts from first principles.
• You like to try new technologies and quickly build exploratory prototypes.
• You thrive in a dynamic, fast-paced environment, embracing change with a proactive and solution-oriented approach.

Nice to have:

• Background in Physics, Engineering or other related computational science.
• Publications relevant to the company domain at top-tier conferences.
• Internship or work experience in one top AI company.
• Strong experience in at least one of the following: reinforcement learning, representation learning, program synthesis, NLP, graph machine learning, knowledge graphs, applied machine learning and data mining, optimization, machine learning for theorem proving, agentic LLMs and RAG, machine learning for science
• Proven contribution to open source projects.

Waddle Labs: - we are an early-stage startup - we build robotics models to solve physical bottlenecks in science (eg. wet lab experiments) - YC W26

The other companies on this career site know what they're doing. We don't. Do you want to help us figure it out?

If you want to find out more, reach out to wave@waddlelabs.ai with 1 sentence about what you’re interested in.

Position: Data Science Intern

Location: 660 5th Avenue, New York, NY

Viking Global Investors (“Viking”) is a global investment firm founded in 1999, managing over $53 billion in capital across public and private investments. With offices in Stamford, New York, Hong Kong, London, and San Francisco, Viking is registered with the U.S. Securities and Exchange Commission. For more information, visit www.vikingglobal.com.

Internship Opportunity

The Data Science Intern will collaborate with the Data Science team, Investment Analysts, and Data Engineers to analyze and expand Viking’s alternative data assets, generating actionable investment insights. This role is ideal for analytical, creative problem solvers eager to apply their data science skills to pressing research questions. Interns will work both independently and alongside quantitative professionals, with flexibility in duration, start dates, and full-time/part-time options.

Informational Webinar: October 30, 6:00–7:00pm ET
Register here

Responsibilities

• Develop and deliver predictive analytics on companies, sectors, and macroeconomic trends
• Generate investment insights from alternative data analysis
• Create methodologies to identify and evaluate private company investment opportunities
• Identify and assess new data sources
• Streamline data lifecycle, operating models, and processes
• Test and evaluate new technologies for the big data platform
• Build centralized, automated analyses and processes
• Share information and insights to support Viking’s research efforts

Qualifications

• Currently enrolled in a Master’s or PhD program (3rd year+) in Data Science, Economics, Finance, Statistics, or related quantitative fields
• Strong communication skills, with the ability to explain complex ideas to non-technical audiences
• Independent thinker, capable of leading research projects with partial supervision
• Proficient in Python, statistical libraries, SQL, BI tools (e.g., Tableau), and cloud technologies
• Sound judgment and big-picture perspective
• Passionate about research, proactive, and self-motivated
• Committed to excellence

Application

Submit your resume and a 1–2 page supplement describing a recent quantitative research project via the Viking career site.
Supplement must include:
- Research question
- Data used
- Approach and statistical methodologies
- Findings
- Computational environment (language, main libraries, etc.)

Application Deadline: November 11, 2025 (11:59 PM EST)
Interviews: Conducted virtually in December

Compensation & Benefits

• Base Salary Range (NYC): $175,000 – $250,000 annually
• Actual compensation determined by skill set, experience, education, and qualifications

Equal Opportunity Employer

Viking is an equal opportunity employer. For questions or accommodation requests, contact:
Viking Campus Recruiting Team
campusrecruiting@vikingglobal.com