Location Hybrid (2-3 days a week) on-site in San Mateo, CA.

BigHat is opening an ML Fellowship. We've got an awesome high-throughput wetlab that pumps proprietary data into custom data and ML Ops infra to power our weekly design-build-train loop. Come solve hard-enough-to-be-fun problems in protein engineering in service of helping patients!

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 Machine Learning (ML) 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 35 million financial instruments searchable, discoverable, and actionable across the global capital markets.

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 AI Engineers with expertise and a passion for Information Retrieval, Search technologies, Natural Language Processing and Generative AI to join our AI Experiences team. Our teams are working on exciting initiatives such as:

-Developing and deploying robust Retrieval-Augmented Generation (RAG) systems, curating high-quality data for model training and evaluation, and building evaluation frameworks to enable rapid iteration and continuous improvement based on real-world user interactions. -Designing and implementing tools that enable LLM-powered search agents to effectively handle complex client queries, shaping Bloomberg's generative AI ecosystem, and scaling these innovative solutions to support thousands of users. -Leveraging both traditional ML approaches and Generative AI to prototype, build, and maintain high-performing, client-facing search and streaming applications that deliver timely and relevant financial insights. -Building robust APIs to facilitate search across diverse collections of data, ensuring highly relevant results and maintaining system stability and reliability.

You'll have the opportunity to: -Collaborate closely with cross-functional teams, including product managers and engineers, to integrate AI solutions into client facing products , enhance analytical capabilities and improve user experience. -Architect, develop, and deploy production-quality search systems powered by LLMs, emphasizing both ML innovation and solid software engineering practices. -Continuously identify areas for improvement within our search systems, proactively experiment with new ideas, and rapidly implement promising solutions—even when improvements rely purely on engineering without direct ML involvement. -Design, train, test, and iterate on models and algorithms while taking ownership of the entire lifecycle, from idea inception to robust deployment and operationalization. -Stay at the forefront of research in IR, NLP, and Generative AI, incorporating relevant innovations into practical, impactful solutions. -Represent Bloomberg at industry events, scientific conferences, and within open-source communities.

As a Machine Learning Researcher at IMC, your work will directly impact our global trading strategies. You will leverage your superior analytical, mathematical, and computing skills to improve existing models and develop new ones. We will empower you to discover your unique niche and excel, taking on responsibility and ownership from the start. Machine Learning Researchers work closely with Traders and Developers in an environment where problem solving, innovation and teamwork are recognized and rewarded.

Location USA, WA, Seattle

Description The Amazon Connect Interactive AI and Engagement organization was formed in April 2025 to bring together Contact Lens, Q in Connect, and Flows/Lex into one organization, responsible for weaving native-AI across the Connect application experiences delivered to end-customers, agents, and managers/supervisors. We are reimagining customer engagement to enable companies to deliver proactive and personalized experiences (in websites, mobile apps, and traditional contact center channels including voice, messaging, and email) that discern and resolve end-customers' intent before problems ever arise. To succeed, we need a unified science strategy and approach to power 'AI-throughout' customer experiences that leverage humans in the loop when required to meet business goals. We seek to hire a Director of Applied Science who will define and execute that strategy, and organization required. This leader will push the technical boundaries in generative AI science, shaping the industry, while influencing and leading key product investments across Connect service teams and leadership.

The business opportunity is substantial. We are executing to be the leader irrespective of the ultimate balance between proactive end-customer self-service and agent-assisted workloads. To do so, science innovation will be pivotal to help achieve our ambitious goals, differentiating Amazon Connect from our competitors.

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)
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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

Location: Palo Alto, CA

Description: Salesforce AI Research is seeking a forward-thinking and accomplished Applied Scientist with deep expertise in AI fairness, accountability, transparency, and explainability (FATE). In this high-impact role, you will operate at the forefront of responsible AI development, working closely with research scientists and engineers in AI Research, as well as cross-functional partners in Responsible AI, Agentforce, and other teams across Salesforce.

You will lead the design and implementation of Trust Layer models, as well as RAI tools and frameworks that ensure our AI systems are fair, accountable, and transparent. Using advanced machine learning techniques, you’ll generate actionable insights, drive research excellence, and support responsible AI practices across the full development lifecycle—from experimentation to production deployment.

We’re looking for a principled and collaborative thought leader who is passionate about bridging the gap between innovation and ethical implementation. You will engage with interdisciplinary teams, strategic partners, vendors, and customers while upholding Salesforce’s core values: trust, customer success, equality, innovation, and sustainability.

Check out our website to learn more about the Salesforce AI Research team https://www.salesforceairesearch.com

Job Responsibilities:

Build state-of-the-art LLM safeguards for enterprise.

Analyze data and models to identify potential trust and safety issues; define testing protocols for different data types and model architectures; recommend mitigation strategies, tooling investments, and safe thresholds for deployment.

Define technical goals and guide research/engineering teams on responsible AI best practices. Offer development support and thought leadership on critical ethical tradeoffs in algorithmic design.

Contribute to the development and adoption of libraries and tools that support evaluation, testing, and mitigation of risks. Build features that enhance explainability and user trust in model outputs.

Collaborate with industry leaders in similar positions in peer organizations on ways to improve the state of responsible AI development.

Minimum Qualifications:

Practical experience in machine learning

MS or Ph.D. in a quantitative discipline with 3+ years of industrial experience, or a BS in a quantitative discipline with 5+ years of industrial experience.

Fluent in building/prototyping machine learning models and algorithms and wrangling large datasets.

Proficient in using Python and common machine learning frameworks (e.g., TensorFlow, PyTorch) and AI tools to implement models and algorithms.

Up to date on the evolution of trusted AI and ability to meet both state-of-the-art and global standards for evaluation, particularly in generative AI.

Experience working across teams of engineers, data scientists, and researchers.

Strong communication skills. Comfortable presenting ideas to peers, cross-functional groups, and executives in multiple formats, from slide decks to informal chats.

Builds trusted relationships across all levels, both internally and externally. Thoughtfully challenges the status quo to enhance team productivity, effectiveness, and culture while maintaining strong, positive partnerships.

Ability to creatively prioritize, stage, and sequence solutions to challenging/complex problems.

Demonstrated experience with actually shipping code, getting data science into production.

Passion for the idea that technology can be a force for social good and for ethics and fairness.

Preferred Qualifications:

Strong experience leading multi-disciplinary teams driving significant business results.

Knowledge of enterprise SaaS space.

Experience with designing and building micro-services, familiar with Kubernetes/containerization/RESTful API/gRPC, etc.

Proficient in SQL, shell scripting, and Unix/Linux command-line tools.

Strong publications at top AI conferences.

Pinely is a privately owned algorithmic trading firm specializing in high-frequency and mid-frequency trading. We’re based in Amsterdam, Cyprus, and Singapore, and we’re experiencing rapid growth. We are looking for a DL Research Group Lead to drive cutting-edge AI research and lead a core DL subgroup. As DL becomes a central engine of the business, your team’s impact will grow across major markets and asset classes.

Responsibilities:

• Lead development of AI models, especially foundational models for market data, to predict prices in noisy, fast-changing markets;
• Set the research agenda, design experiments, and validate results;
• Build and manage a high-performing research team;
• Ensure a fast, transparent, value-driven research process;
• Integrate contributions from multiple researchers into production-ready solutions;
• Contribute hands-on to coding and strategy development;
• Expand responsibilities within the DL department over time.

Requirements:

• Strong DL researcher with technical leadership experience;
• Preferably experienced in high-end AI domains (LLMs, reasoning, generative models);
• Motivated by deep research and real-world impact;
• Able to maintain high pace while supporting a healthy team culture;
• Trading experience optional — first-principles thinking is key.

What we offer:

• Relocation package to Amsterdam
• High impact on a core business function and direct influence on real PnL;
• Minimal bureaucracy, fast feedback loops, massive datasets, reproducible experiments;
• Strong engineering support and an H200-based Data Center growing 2× yearly;
• Work on extremely challenging, non-stationary markets with low signal-to-noise;
• Opportunity to build foundational models for finance and shape the future of quant AI;
• Freedom to pursue deep research and define your modeling vision;
• A top-tier team, on-site in Amsterdam, working directly with founders;
• Influence over team hiring and development.
• Internal training, comprehensive health insurance, sports reimbursement, and biannual corporate events

San Francisco

About this role

We’re looking for a Data Engineer to help design, build, and scale the data infrastructure that powers our analytics, reporting, and product insights. As part of a small but high-impact Data team, you’ll define the architectural foundation and tooling for our end-to-end data ecosystem.

You’ll work closely with engineering, product, and business stakeholders to build robust pipelines, scalable data models, and reliable workflows that enable data-driven decisions across the company. If you are passionate about data infrastructure, and solving complex data problems, we want to hear from you!

Tech stack

Core tools: Snowflake, BigQuery, dbt, Fivetran, Hightouch, Segment Periphery tools: AWS DMS, Google Datastream, Terraform, GithHub Actions

What you’ll do

Data infrastructure: * Design efficient and reusable data models optimized for analytical and operational workloads. * Design and maintain scalable, fault-tolerant data pipelines and ingestion frameworks across multiple data sources. * Architect and optimize our data warehouse (Snowflake/BigQuery) to ensure performance, cost efficiency, and security. * Define and implement data governance frameworks — schema management, lineage tracking, and access control.

Data orchestration: * Build and manage robust ETL workflows using dbt and orchestration tools (e.g., Airflow, Prefect). * Implement monitoring, alerting, and logging to ensure pipeline observability and reliability. * Lead automation initiatives to reduce manual operations and improve data workflow efficiency.

Data quality: * Develop comprehensive data validation, testing, and anomaly detection systems. * Establish SLAs for key data assets and proactively address pipeline or data quality issues. * Implement versioning, modularity, and performance best practices within dbt and SQL.

Collaboration & leadership: * Partner with product and engineering teams to deliver data solutions that align with downstream use cases. * Establish data engineering best practices and serve as a subject matter expert on our data pipelines, models and systems.

What we’re looking for

• 5+ years of hands-on experience in a data engineering role, ideally in a SaaS environment.
• Expert-level proficiency in SQL, dbt, and Python.
• Strong experience with data pipeline orchestration (Airflow, Prefect, Dagster, etc.) and CI/CD for data workflows.
• Deep understanding of cloud-based data architectures (AWS, GCP) — including networking, IAM, and security best practices.
• Experience with event-driven systems (Kafka, Pub/Sub, Kinesis) and real-time data streaming is a plus.
• Strong grasp of data modeling principles, warehouse optimization, and cost management.
• Passionate about data reliability, testing, and monitoring — you treat pipelines like production software.
• Thrive in ambiguous, fast-moving environments and enjoy building systems from the ground up.

San Francisco, CA, US; Palo Alto, CA, US; Seattle, WA, US; New York, NY, 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.

Within the Monetization ML Engineering organization, we try to connect the dots between the aspirations of Pinners and the products offered by our partners. As a Distinguished Machine Learning Engineer, you will be responsible for developing and executing a vision for the evolution of the machine learning technology stack for Monetization. You will work on tackling new challenges in machine learning and deep learning to advance the statistical models that power ads performance and ads delivery that bring together Pinners and partners in this unique marketplace.

What you'll do:

• Lead user-facing projects that involve end-to-end engineering development in both frontend and backend and ML.
• Improve relevance and increase long term value for Pinners, Partners, Creators, and Pinterest through efficient Ads Delivery.
• Improve our engineering systems to improve the latency, capacity, stability and reduce infra cost.
• Collaborate with product managers and designers to develop engineering solutions for user-facing product improvements.
• Collaborate with other engineering teams (infra, user modeling, content understanding) to leverage their platforms and signals.
• Champion engineering excellence and a data driven culture, mentor senior tech talent and represent Pinterest externally in the tech and AI communities.

What we’re looking for:

• Degree in computer science, machine learning, statistics, or a related field.
• 15+ years of working experience in engineering teams that build large-scale, ML‑driven, user‑facing products.
• Experience leading cross‑team engineering efforts that improve user experience in products.
• Understanding of an object‑oriented programming language such as Go, Java, C++, or Python.
• Experience with large‑scale data processing (e.g., Hive, Scalding, Spark, Hadoop, MapReduce).
• Strong software engineering and mathematical skills, with knowledge of statistical methods.
• Experience working across frontend, backend, and ML systems for large‑scale user‑facing products, with a good understanding of how they all work together.
• Hands‑on experience with large‑scale online e‑commerce systems.
• Background in computational advertising is preferred.
• Excellent cross‑functional collaboration and stakeholder communication skills, with strong execution in project management.