ai research engineer

Hex Technologies

SF or NYC
 About the role
 
Hex is an AI-powered platform for modern Data Science and Data Analytics workflows. AI Research Engineers at Hex partner with product teams to build industry-leading AI experiences such as the Notebook Agent. In the process, AI Research Engineers will run experiments, fine-tune models, deploy AI infrastructure, and build and maintain experimentation tooling.
 
As an AI Research Engineer partnered with Hex's product teams, your focus will be driving Hex's context engine and pushing forward the capabilities of our Notebook Agent. Built for people doing the most complex and impactful data work in an organization, the Notebook Agent is a highly technical data copilot that writes SQL and python, builds beautiful reports and visualizations, and collaborates with the analyst on new avenues of inquiry. Whether its pushing the frontiers of SQL generation quality or using LLMs to evaluate agent threads, your job will be to enable the data teams that work in Hex to build out highly accurate and curated data experiences for their stakeholders, unlocking the power of data driven decisions for the rest of the business.
 
If you’re a strong builder excited to bring these capabilities to thousands of users, come do it on the best Data Science platform around, with the best user context.
 
We are looking for a senior engineer (from an AI Eng, SWE or MLE background) eager to rapidly expand our capabilities in several greenfield applications. As one of our team’s early hires, you will work on a variety of initiatives including:
 
Building features and experiences from 0 to 1
 Partnering on determining the architecture and stack for our AI-enabled capabilities
 Shipping product experiences that fundamentally change the way that Data Scientists and Analysts operate
 Working at the cutting edge of production AI applications
 
This type of ownership will provide incredible opportunities for personal and professional growth. You will have ample technical and team leadership opportunities, depending on your interests.
 
We aim to deliver AI capabilities that radically accelerate and augment the data science workflow – we’ve got an exciting roadmap and are willing to share more details during the process. We’re particularly interested in candidates who bring inspired excitement about what is possible in this space.
 
We'd love to hear from you if you have: 
Experience getting AI/ML capabilities into production and serving real users – we’re not currently looking for new grad folks.
 A lot of enthusiasm for applications of AI to real business problems.
 Understanding of core MLOps/SW Architecture concepts for modern ML-based applications.
 Ideal candidates are strong on Infra aspects of MLOps as well.
 You’re comfortable working in both Python & JS/TS – it’s okay if you’re only strong in one, but openness to both is important.
 Experimentalist mindset – understanding that quick iteration, and discerning critical thinking, can yield rapid progress on new challenges.
 Interest in the data space, and a love of shipping great products and building tools that empower end users to do more.
 Experience maintaining a high quality bar for design, correctness, and testing.
 Our stack
 
Our product is a web-based notebook and app authoring platform. Our frontend is built with Typescript and React, using a combination of Apollo GraphQL and Redux for managing application state and data. On the backend, we also use Typescript to power an Express/Apollo GraphQL server that interacts with Postgres, Redis, and Kubernetes to manage our database and Python kernels. Our backend is tightly integrated with our infrastructure and CI/CD, where we use a combination of Terraform, Helm, and AWS to deploy and maintain our stack.
 
This is a full-time role based out of either our San Francisco or New York office. Employees are encouraged to come into the office at least twice a week, with Tuesdays and Thursdays being our main in-person days.
 
In addition to our unique culture, Hex proudly offers a competitive total rewards package, including but not limited to, market-benched salary & equity, comprehensive health benefits, and flexible paid time off.
 
The salary range for this role is: $214,000 - $285,000
 
The salary range shown may be a reflection of additional factors such as geographical location and skill ranges/levels we’re open to. Placement in the salary range will be decided upon completion of the interview process, taking into account factors like leaving room for growth, internal fairness & parity, your demonstrated skills, and the depth of your experience. Our Recruiting team will be able to provide more details during the interview process.
 
By submitting an application the candidate consents to the use of their personal information in accordance with the Hex Privacy policy: https://learn.hex.tech/docs/trust/privacy-policy.
 
About Hex
 
Hex is growing our team of builders on a mission to make everyone a data person. Our platform solves key pain points with today's data and analytics tooling, and empowers anyone to explore data using natural language, with or without code, on trusted context. Thousands of customers like Ramp, Figma, Stubhub, Anthropic, and Gamma love Hex for our beautiful UI, agentic superpowers, and boundless flexibility.
 
Hex has raised over $100M from leading investors like Sequoia, a16z, Snowflake and Amplify. With office hubs in San Francisco and New York, as well as remote team members throughout the US and UK, we're a high-agency team that ships fast and has fun doing it. Check out our Intro to Hex video and employee handbook to learn more about what it's like to work at Hex.

AI Research Engineer

SARJ

<div>Sarj.ai is hiring an AI/ML Engineer to train and deploy speech models that power our voice communications platform. We work in Python and PyTorch on GCP. Strong deep learning fundamentals highly appreciated.<h3 class="jobSectionHeader">
What you'll do</h3><ul><li>
Train large-scale speech models (STT/TTS)</li><li>
Work with modern speech architectures and push them to production</li><li>
Build and maintain ML training pipelines for real-time voice processing</li><li>
Develop evaluation frameworks and improve model performance</li><li>
Collaborate with product and engineering to ship AI-powered features</li></ul><h3 class="jobSectionHeader">
What we're looking for</h3><ul><li>
2+ years working with ML in production</li><li>
Strong Python + PyTorch/PyTorch Lightning</li><li>
Understanding of deep learning fundamentals</li><li>
Experience with speech/audio ML is a strong plus</li><li>
Experience with large-scale or distributed training</li><li>
Familiarity with GCP (Vertex AI, Cloud Run, BigQuery)</li></ul></div>

Cotiviti

<div>Overview:
<div>
The Generative AI Research Engineer Intern conducts primary and secondary research of advanced and emerging healthcare informatics technology with a focus on Generative AI and emerging Artificial General Intelligence technology for healthcare treatment, payment, and operations use cases. Creates research papers, analytical reports, proposals, and educational material. Maintains a deep understanding of technology trends and hands-on experience with relevant technologies. Develops generative AI models, architectures, databases, and systems to improve healthcare solutions.</div><div></div><div> 
We are currently looking for interns who can start in the Summer or Fall of 2026.</div>
Responsibilities:

NOTE: There are multiple open intern positions. Hours and length of assignment will be at the intern's choice from 20 - 40 hours per week with a minimum of one semester up to one year. 
Technical Expertise<ul><li>
Demonstrates a strong understanding of technology trends, research, and emerging technologies relevant to the healthcare industry, particularly in Generative AI.</li><li>
Assists in developing and improving LLMs and ML tools used across the organization.</li><li>
Assists in establishing and maintaining an Artificial Intelligence Governance Program.</li></ul>
Communication &amp; Collaboration<ul><li>
Communicates technology-related updates and requirements to other departments and contributes to presentations for senior management.</li><li>
Collaborates with research and development teams, product management, and strategic analysts to support ongoing projects.</li></ul>
Leadership &amp; Management<ul><li>
Partners with Business Units to provide reliable intelligence, validated technology options, and insights on enterprise and industry trends.</li><li>
Supports technology project teams by coordinating specific tasks, assisting with day-to-day operations, and contributing to the successful delivery of solutions.</li><li>
Assists in collaborative efforts with academic research teams, practicums, internships, and vendor POCs.</li></ul>
External Relationships &amp; Partnerships<ul><li>
Supports vendor evaluations and contributes to collaborations with vendors.</li><li>
Assists as a liaison between academic institutions, professional organizations, and research groups as needed.</li></ul>
Other<ul><li>
Support the Academic Corporate Engagement efforts to develop research and educational talent, with a focus on enhancing health tech knowledge and skills.</li><li>
Complete all responsibilities and goals outlined in the internship program.</li><li>
Complete all special projects and other duties as assigned.</li><li>
Must be able to perform duties with or without reasonable accommodation.</li></ul> 
This job description is intended to describe the general nature and level of work being performed in this internship. It is not an exhaustive list of responsibilities, duties, and skills required and does not constitute an employment agreement. This job description is subject to change as Cotiviti&rsquo;s needs and requirements of the internship evolve.
Qualifications:
<ul><li>Currently pursuing or recently completed an advanced degree in healthcare, technology, or a related field (e.g., Biomedical Informatics, Computer Science) with preference of a PhD.</li><li>
Demonstrated interest or experience in AI, healthcare technology, or informatics research.</li><li>
Strong foundational knowledge in generative AI model development, architectures, and vector databases.</li><li>
Hands-on experience with working with Machine Learning and Deep Learning models. Experience with LLM/RAG models and LLM fine-tuning is a plus.</li><li>
Hands-on experience working with cloud services (AWS/Azure), large data sets, and building data pipelines for ML solutions. Experience with vector embeddings and databases is a plus.</li><li>
Ability to work collaboratively and communicate effectively with cross-functional teams.</li></ul><div>
Mental Requirements:</div><ul><li>
Communicating with others to exchange information.</li><li>
Assessing the accuracy, neatness, and thoroughness of the work assigned.</li></ul><div>
Physical Requirements and Working Conditions:</div><ul><li>
Remaining in a stationary position, often standing or sitting for prolonged periods.</li><li>
Repeating motions that may include the wrists, hands, and/or fingers.</li><li>
Must be able to provide a dedicated, secure work area.</li><li>
Must be able to provide high-speed internet access/connectivity and office setup and maintenance.</li><li>
No adverse environmental conditions are expected.</li></ul><div>
Base compensation ranges from $32.00 to $40.00 per hour. Specific offers are determined by various factors, such as experience, education, skills, certifications, and other business needs.</div><div></div><div> 
Nonexempt employees are eligible to receive overtime pay for hours worked in excess of 40 hours in a given week, or as otherwise required by applicable state law.</div><div></div><div> 
Date of posting: 4/24/2026</div><div>
Applications are assessed on a rolling basis. We anticipate that the application window will close on 7/24/2026, but the application window may change depending on the volume of applications received or close immediately if a qualified candidate is selected.</div></div><div></div>

Intern - Generative AI Research Engineer

C2R Ventures

<div>
 
 Elite multi-strategy hedge fund manager that invests globally in a wide array of assets and strategies, is seeking an elite Agentic AI Research Engineer to play a key role in the ongoing development and enhancement of their investment process.
 
 
 
 
 
 Do not need financial experience to apply, but of course it is welcome. Candidates from AI research arms/divisions of notable bigtech companies and/or AI start-ups with elite VC backing are very welcome to apply.
 
 
 
 
 
 This Engineer will be embedded in investment teams to augment their investment process through designing and building multi-agent frameworks by developing deep understanding of each business and leveraging cutting-edge methods.
 
 
 
 
 
 This is a Full Stack role that will encompass the building of foundational infrastructure and developing robust data pipelines through agentic design.
 
 
 
 
 
 
 Responsibilities:
 
 
 <ul>
 <li>
 Work with investment teams to find solutions to their most vexing challenges, applying agents to assist in solving problems
 </li>
 <li>
 Design, build, and integrate a multi-agent AI framework that can orchestrate deep research in and across vastly different subject matter and domain expertise
 </li>
 <li>
 Implement rigorous quantitative benchmarks for large scale agentic tasks
 </li>
 <li>
 Assist with automated evaluation of AI models and prompts across a wide variety of project and investment teams
 </li>
 <li>
 Help create and optimize data mixes for model training that maximize agent performance or ease of use on agentic tasks
 </li>
 </ul>
 
 
 
 
 
 Requirements:
 
 
 <ul>
 <li>
 0&gt;1 builder who is comfortable with uncertainty, operates with high agency, and excels at rapid iteration and shipping
 </li>
 <li>
 Experience developing complex agentic systems using LLMs with an emphasis on agentic harness design (e.g., communication architectures for agents)
 </li>
 <li>
 Successfully demonstrated the ability of taking a product from conception to completion
 </li>
 <li>
 Understanding of LLM-as-judge, reward hacking, specification gaming robustness problems
 </li>
 <li>
 Have strong Python skills and can build robust infrastructure across the stack
 </li>
 </ul>
</div>

Artificial Intelligence Engineer

Digitrends

AI EngineerKey Responsibilities<ul><li>Design, develop, and fine-tune LLM-based AI models for real-world applications.</li><li>Implement custom LLM training, reinforcement learning, and fine-tuning using open-source and proprietary models like GPT, Llama, Mistral, Claude, or Falcon.</li><li>Optimize model efficiency, inference speed, and resource utilization for deployment in cloud or on-premise environments.</li><li>Build data pipelines for training and evaluating AI models.</li><li>Implement prompt engineering, retrieval-augmented generation (RAG), and memory-based techniques for improved performance.</li><li>Integrate LLMs into applications using APIs, LangChain, vector databases (e.g., Pinecone, FAISS, ChromaDB).</li><li>Develop custom embeddings, transformers, and tokenization strategies for specific use cases.</li><li>Work closely with MLOps, backend engineers, and data scientists to ensure smooth deployment and monitoring of AI solutions.</li><li>Research and stay updated on emerging trends in NLP, generative AI, and model compression techniques.</li><li>Ensure compliance with ethical AI principles and data security standards when handling sensitive data.</li></ul>Required Skills:<ul><li>Strong knowledge of Python and frameworks like PyTorch, TensorFlow, JAX.</li><li>Experience with Hugging Face Transformers, OpenAI API, LangChain, and vector databases.</li><li>Understanding of LLM architectures, fine-tuning techniques (LoRA, QLoRA, PEFT), and model distillation.</li><li>Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).</li><li>Familiarity with distributed computing, GPU acceleration (CUDA, TensorRT), and multi-node training.</li><li>Knowledge of AI safety, bias mitigation, and responsible AI development.</li><li>Strong problem-solving, debugging, and optimization skills.</li><li>Excellent communication and teamwork skills.</li></ul>Preferred Qualifications<ul><li>Experience in building domain-specific AI assistants or chatbots.</li><li>Knowledge of multimodal AI, speech-to-text, text-to-image models.</li><li>Contributions to open-source AI projects or research papers in NLP/LLMs.</li></ul>Key Benefits<ul><li>Working in a fast-paced tech start-up environment</li><li>Attractive salary and incentives for high-quality work</li><li>Flexible schedule</li><li>Health Insurance</li><li>Five Working Days</li><li>Provident Fund</li></ul>Job Type: Full-timeWork Location: In person

AI Engineer

Bank of America

<div>
 
 Job Description:
 
 
 
 At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day.
 
 
 Being a Great Place to Work is core to how we drive Responsible Growth. This includes our commitment to being an inclusive workplace, attracting and developing exceptional talent, supporting our teammates&rsquo; physical, emotional, and financial wellness, recognizing and rewarding performance, and how we make an impact in the communities we serve.
 
 
 Bank of America is committed to an in-office culture with specific requirements for office-based attendance and which allows for an appropriate level of flexibility for our teammates and businesses based on role-specific considerations.
 
 
 At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!
 
 
 
 The Data and AI team within Global Payment Solutions (GPS) at Bank of America
 
 is looking for a highly technical Research Engineer that is a self-starter who can translate complex concepts and generate actionable insights.
 
 
 
 Who we are:
 
 
 
 The GPS Data and AI team drives and powers innovation within the one of the largest payment businesses in the world. We are the core data scientists building end-to-end production level solutions at scale. The team is a collection of individuals that welcomes challenging problems because that is where the learning begins. Many of our projects begin with &ldquo;think tank&rdquo; sessions with business teams that is later translated to tangible solutions and products.
 
 
 
 Representative Projects:
 
 
 
 <ul>
 <li>
 Develop advanced statistical methods to determine the optimal interest-rate or product pricing strategies for clients
 </li>
 <li>
 Build a Generative AI-powered search platform that enables sales and product teams to access high quality answers to product, servicing, and client related questions
 </li>
 <li>
 Develop AI models that shift foreign currency conversion &ldquo;up the payment stream,&rdquo; reducing reliability on beneficiary banks
 </li>
 <li>
 Apply advanced NLP techniques to generate near real-time insights into what clients are reaching out to servicing teams about, helping servicing teams anticipate client needs and improve service quality
 
 
 </li>
 </ul>
 
 Who we&rsquo;re looking for:
 
 
 
 As a Research Engineer on the GPS team, you will tackle one of our most import challenges: building models that transform data into revenue-driving insights and products. This role blends research, engineering, and product responsibilities, requiring you to design statistical models, build scalable ML pipelines, and deploy algorithms directly into our production systems. You will work across teams to solve problems in recommendation, stochastic optimization, and time-series forecasting; while running large A/B tests on new methods we design to push the boundaries of what data can achieve.
 
 
 If you are passionate about working in cross-functional teams and utilizing your skills for technical product management, statistical analytics, predictive modeling, and generating revenue, consider applying to this role.
 
 
 
 Responsibilities:
 
 
 
 <ul>
 <li>
 Frame abstract business problems using advanced data science and machine learning algorithms
 </li>
 <li>
 Work with stakeholders throughout the organization to identify opportunities for leveraging internal and external data to drive business solutions
 </li>
 <li>
 Own critical research and application development, strengthening the firm's competitive advantage
 </li>
 <li>
 Shape cross-team collaboration to advance the firm's data science capabilities
 
 
 </li>
 </ul>
 
 Required Skills:
 
 
 
 <ul>
 <li>
 Minimum Bachelor&rsquo;s degree in a quantitative field such as computer science, math, statistics, and physics
 </li>
 <li>
 Minimum 3 years of experience with translating mathematical models and algorithms into code (Python and/or C++)
 </li>
 <li>
 Strong foundation in probability, statistics, and applied machine learning (NLP, time-series analysis, Generative AI)
 </li>
 <li>
 Prior experience working in a highly technical data driven research environment
 </li>
 <li>
 Ability to communicate complex topics in a concise and coherent manner
 
 
 </li>
 </ul>
 
 Desired Skills:
 
 
 
 <ul>
 <li>
 Graduate level degree in a quantitative field such as, computer science, math, statistics, and physics
 </li>
 <li>
 Demonstrated prior experience through work, research or passion projects in RAG, Agentic Frameworks, LLMs, Reinforcement Learning
 </li>
 <li>
 Are energized by the high stakes and intensity of dynamic environments and ready to dive in whenever
 </li>
 <li>
 Are excited to dive into new technical areas on a regular basis
 
 
 </li>
 </ul>
 
 Shift:
 
 
 
 1st shift (United States of America)
 
 
 
 Hours Per Week:
 
 
 
 40
</div>

Data Scientist I

MASTER-WORKS

<div>Master Works is seeking an AI Engineer with strong generative AI prototyping experience to rapidly turn ideas into working AI-powered demos, proofs of concept, and early-stage products. The role sits between research and production engineering &mdash; combining hands-on use of large language models, multimodal models, retrieval-augmented generation, and agent frameworks to validate feasibility, explore new capabilities, and de-risk feature delivery. The role is central to accelerating AI innovation across the data, analytics, and intelligence portfolio, with a particular emphasis on bilingual (Arabic/English) AI use cases.<ul><li>
Rapidly design and build generative-AI prototypes and proofs of concept &mdash; from initial idea to working demo &mdash; using modern LLM APIs, open-source models, and prototyping frameworks.</li><li>
Design and implement retrieval-augmented generation (RAG) pipelines, including document ingestion, chunking strategies, embedding generation, vector storage, and retrieval orchestration.</li><li>
Build agentic systems that use tool/function calling, planning, and multi-step reasoning to automate complex tasks; integrate AI agents with internal APIs, databases, and external services.</li><li>
Engineer prompts, system instructions, and structured-output schemas; iterate on prompt design through measurable evaluation rather than guesswork.</li><li>
Work with multimodal AI capabilities &mdash; text, vision, speech (STT/TTS), and document understanding &mdash; and combine them into coherent end-to-end AI pipelines.</li><li>
Build and run AI evaluation frameworks (offline benchmarks, LLM-as-judge, golden-set regression testing) to measure quality, accuracy, latency, and cost across model and prompt variants.</li><li>
Adapt and fine-tune open-source models (LoRA, QLoRA, full fine-tuning) when proprietary or domain-specific behaviour is required, especially for Arabic-language tasks.</li><li>
Apply responsible-AI practices &mdash; safety filtering, hallucination mitigation, prompt-injection defence, PII handling, and bias awareness &mdash; especially for sensitive or regulated environments.</li><li>
Hand off mature prototypes to production engineering teams, providing clear documentation, evaluation results, deployment notes, and migration guidance.</li><li>
Demo prototypes and AI capabilities to internal stakeholders and clients; explain technical concepts, limitations, and risks to non-technical audiences.</li><li>
Track and evaluate fast-moving developments in the generative-AI ecosystem (new models, tools, techniques, and providers) and recommend adoption where they materially improve outcomes.</li><li>
Collaborate cross-functionally with product, design, data, and software engineering teams to shape AI features end-to-end and ensure they deliver real user value.</li></ul> 

Requirements 
<ul><li>
Bachelor&rsquo;s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, or a related discipline.
</li><li>Postgraduate qualification (MSc/PhD) in Machine Learning, Artificial Intelligence, Natural Language Processing, or a related field is preferred.</li><li>
Recognised certifications in machine learning, deep learning, generative AI, or cloud AI platforms (AWS, Azure, GCP) are a strong plus.</li><li>
3&ndash;5+ years of AI/ML engineering experience, with at least 1&ndash;2 years hands-on building generative-AI applications using modern LLMs.</li><li>
Demonstrable portfolio of shipped prototypes or production AI features &mdash; ideally including RAG systems, AI agents, or multimodal pipelines.</li><li>
Hands-on experience with leading LLM APIs (e.g., Anthropic Claude, OpenAI GPT, Google Gemini) and open-source model serving (e.g., Hugging Face, vLLM, Ollama).</li><li>
Strong Python proficiency, including modern AI libraries such as PyTorch, Hugging Face Transformers, LangChain or LlamaIndex, and standard data tooling.</li><li>
Working experience with embedding models, vector databases (e.g., Pinecone, Weaviate, Qdrant, FAISS), and retrieval evaluation techniques.</li><li>
Familiarity with rapid-prototyping tools (Streamlit, Gradio, Jupyter), API integration, and lightweight web back-ends.</li><li>
Experience designing AI evaluation harnesses (offline benchmarks, LLM-as-judge, golden sets) and using observability/tracing tools for AI systems.</li></ul><ul><li>
Exposure to fine-tuning techniques (LoRA, QLoRA, instruction tuning) and to Arabic-language NLP is strongly preferred.</li><li>
Working knowledge of containerisation (Docker), version control (Git), and cloud AI platforms (AWS Bedrock, Azure OpenAI, GCP Vertex AI) is a strong plus.</li><li>
Excellent leadership and team development skills.</li><li>
Strong bias for action and a rapid-prototyping mindset; able to ship a working demo in days, not months.</li><li>
Comfortable working under uncertainty &mdash; rapidly forming hypotheses, running experiments, and iterating based on evidence.</li><li>
Strong analytical and problem-solving skills, with the discipline to evaluate AI behaviour quantitatively rather than relying on intuition alone.</li><li>
Excellent verbal and written communication, with the ability to demo AI capabilities and explain technical concepts, limitations, and risks to non-technical audiences.</li><li>
Curiosity and continuous-learning mindset; actively follows the rapidly evolving generative-AI landscape and brings new ideas back to the team.</li><li>
Collaborative team player; comfortable in cross-functional teams of researchers, software engineers, designers, and client business owners.</li><li>
Cultural awareness and sensitivity, particularly when designing AI experiences for Arabic-speaking users in regional contexts.</li></ul></div>

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