applied ai engineer

BV Teck

<div><p><b>Bright Vision Technologies</b> is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.</p><p><b>
Job Title:</b> Applied AI Engineer<br>
<b>Location:</b> 100% Remote (Continental United States)<br>
<b>Position Type:</b> Full-time, Direct W2<br>
<b>Salary Range:</b> $100,000&ndash;$150,000 Annually<br>
<b>Experience Required:</b> 6+ Years<br>
<br>
<b>Sponsorship:</b> U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position.</p><h3 class="jobSectionHeader"><b>
Job Summary:</b></h3><p>
We are seeking an <b>Applied AI Engineer</b> to design, develop, and deploy production-ready AI and machine learning solutions. The ideal candidate will have expertise in <b>Python, PyTorch or JAX, deep learning, LLMs, computer vision, NLP, and ML pipelines</b>, with experience taking AI models from research to production while optimizing performance, scalability, and reliability.</p><h3 class="jobSectionHeader"><b>
Key Responsibilities:</b></h3><ul><li>
Design, build, and deploy AI/ML solutions for real-world business problems.</li><li>
Develop and optimize training and inference pipelines.</li><li>
Train, fine-tune, and evaluate deep learning and LLM models.</li><li>
Collaborate with cross-functional teams to deliver scalable AI applications.</li><li>
Monitor model performance, data quality, and production reliability.</li><li>
Document solutions and contribute to AI best practices.</li></ul><h3 class="jobSectionHeader"><b>
Required Qualifications:</b></h3><ul><li>
6+ years of experience in applied AI, machine learning, or deep learning.</li><li>
Strong proficiency in <b>Python</b> and <b>PyTorch or JAX</b>.</li><li>
Experience with LLMs, NLP, computer vision, distributed training, and ML deployment.</li><li>
Strong understanding of machine learning, statistics, and model evaluation.</li></ul><h3 class="jobSectionHeader"><b>
Preferred Qualifications:</b></h3><ul><li>
Experience with LLM fine-tuning, RAG, agentic AI, or multimodal AI.</li><li>
Publications, open-source ML contributions, or experience with Responsible AI.</li></ul><p><b>
Interested in this opportunity? Apply today for immediate consideration!</b></p><p>
Email your updated resume: jaya@bvteck.com<br>
Call or Text: (908) 505-3545<br>
Learn more: www.bvteck.com</p><p><b>
Bright Vision Technologies is an Equal Opportunity Employer.</b></p><p>
Equal Employment Opportunity (EEO) Statement</p>
<p>Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall.</p>
<p>BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment.</p><p>
</p><p>hRyF7l0Fgk</p></div>

Applied AI Engineer

NVIDIA

<div>
 NVIDIA's Silicon Co-Design Group is seeking an Applied AI Engineer to innovate, develop, and integrate innovative AI solutions into the design and automation infrastructure that powers our chips. Every CPU, GPU, and Tegra SoC NVIDIA has shipped in the past four years passed through our toolchain on its way to production &mdash; over 200 product SKUs were optimized during the Blackwell generation alone. Now we're rebuilding that toolchain around AI, and we're looking for the engineer to lead that charge. In this role, you will architect and implement solutions that enhance the efficiency, scalability, and intelligence of our workflows, driving initiatives from concept to deployment. If you combine deep technical expertise with a hands-on approach and an aim to push the boundaries of what's possible, this is your opportunity. At NVIDIA, we strive for perfection, encourage innovation, and provide opportunities to explore new ways to succeed!
 <br/>
 <br/>
 <strong>
  What You'll Be Doing
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   LLM-Powered Validation Pipelines: Design and deploy AI systems that make post-silicon validation faster, smarter, and more scalable across semiconductor environments. You're not maintaining what exists, you're building what comes next.
  </li>
  <li>
   Cross-Team AI Integration: Work directly with multi-functional engineering teams across the organization to identify where AI can eliminate friction, and then build the solution. Your output will be felt across teams, products, and generations of silicon.
  </li>
  <li>
   Technology Scouting &amp; Evaluation: Evaluate emerging AI frameworks and architectures before the rest of the industry catches on. Be the person who spots what's worth adopting, and makes the case for it.
  </li>
  <li>
   Impact Measurement &amp; Continuous Improvement: Build the data systems that prove what's working. Establish clear, quantitative indicators of AI impact, close performance gaps, and drive iteration across the org to turn insight into lasting improvement!
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  What We Need To See
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   BS, MS, or PhD or equivalent experience in CS, EE, CE, or a related field, with 5+ years of hands-on experience building and deploying ML/AI systems or data-intensive backend services.
  </li>
  <li>
   2+ years of direct Applied AI experience independently owning an AI agent, LLM-powered workflow, or intelligent automation system end-to-end &mdash; from prototype through production deployment.
  </li>
  <li>
   Strong Python skills and proficiency in at least one static language such as C, C++, C#, Java, or Scala.
  </li>
  <li>
   Experience working within a silicon development environment, with exposure to chip and system characterization methodologies, process variation, statistical error rates, or advanced timing/power analysis.
  </li>
  <li>
   Hands-on experience with silicon bring-up, characterization, or lab debug using standard tools (e.g., oscilloscopes, multimeters, logic analyzers).
  </li>
  <li>
   Strong EE fundamentals, including computer architecture, high-speed interfaces, timing, power basics, and a solid understanding of firmware/driver structures and hardware interaction.
  </li>
  <li>
   Proven track record to balance multiple concurrent projects and apply excellent problem-solving, communication, and teamwork skills.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Ways To Stand Out From The Crowd
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experience debugging complex system-level issues involving HW/SW interactions, including leadership or ownership in driving root cause analysis of silicon or feature-level issues.
  </li>
  <li>
   Ability to translate innovative AI research into practical, high-impact production tools.
  </li>
  <li>
   Familiarity with modern AI technologies and methodologies for crafting and launching LLMs.
  </li>
  <li>
   Experience with building and deploying orchestration agents managing hundreds to thousands of tools.
  </li>
  <li>
   Demonstrated experience with deep learning frameworks like PyTorch or TensorFlow, and hands-on experience with agentic and orchestration tools including NeMo Agent Toolkit, LangChain, Semantic Kernel, AutoGen, CrewAI, or n8n.
   <br/>
   <br/>
  </li>
 </ul>
 Our team is at the forefront of silicon innovation, advancing groundbreaking technologies. We offer a dynamic work environment where your contributions will directly impact the company's success. Join us to advance your career in a role where you can truly make a difference. With competitive salaries and a generous benefits package, we are widely considered one of the technology industry&rsquo;s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us, and due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you!
 <br/>
 <br/>
 Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.
 <br/>
 <br/>
 You will also be eligible for equity and benefits.
 <br/>
 <br/>
 Applications for this job will be accepted at least until August 1, 2026.
 <br/>
 <br/>
 This posting is for an existing vacancy.
 <br/>
 <br/>
 NVIDIA uses AI tools in its recruiting processes.
 <br/>
 <br/>
 NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
 <br/>
 <br/>
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 <br/>
 <br/>
</div>


Future Group Language Solutions

<div>
 <strong>
  About The Role
  <br/>
  <br/>
 </strong>
 We are looking for an
 <strong>
  Applied AI Engineer
 </strong>
 to design, build, and deploy intelligent AI solutions that solve real business challenges. In this role, you'll work with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), GraphRAG, AI agents, and knowledge graphs to create scalable, production-ready AI applications.
 <br/>
 <br/>
 This is an
 <strong>
  AI-first engineering role
 </strong>
 , where leveraging AI development tools such as ChatGPT, Cursor, GitHub Copilot, Claude, or Windsurf is an essential part of the development workflow.
 <br/>
 <br/>
 Key Responsibilities
 <br/>
 <br/>
 <ul>
  <li>
   Design, develop, and deploy AI-powered applications using LLMs.
  </li>
  <li>
   Build and optimize RAG and GraphRAG pipelines.
  </li>
  <li>
   Develop AI agents and multi-agent workflows for business automation.
  </li>
  <li>
   Design and manage knowledge graphs using GraphDB technologies.
  </li>
  <li>
   Integrate enterprise data sources with AI applications.
  </li>
  <li>
   Engineer prompts, workflows, and agent orchestration for reliable AI systems.
  </li>
  <li>
   Evaluate and optimize AI models for quality, latency, scalability, and cost.
  </li>
  <li>
   Build production-ready APIs and AI services.
  </li>
  <li>
   Collaborate with cross-functional teams to deliver AI-driven products.
  </li>
  <li>
   Stay up to date with the latest AI models, frameworks, and best practices.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Requirements
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelor's degree in Computer Science, Software Engineering, AI, or a related field.
  </li>
  <li>
   3+ years of experience developing AI-powered or data-intensive applications.
  </li>
  <li>
   Strong proficiency in Python.
  </li>
  <li>
   Hands-on experience with LLMs (OpenAI, Azure OpenAI, Anthropic, Gemini, or similar).
  </li>
  <li>
   Experience implementing Retrieval-Augmented Generation (RAG).
  </li>
  <li>
   Experience with Graph Databases such as Neo4j, Amazon Neptune, Memgraph, or GraphDB.
  </li>
  <li>
   Familiarity with vector databases such as Pinecone, Qdrant, Weaviate, Milvus, or pgvector.
  </li>
  <li>
   Experience integrating AI models through APIs and SDKs.
  </li>
  <li>
   Solid understanding of REST APIs, Git, Docker, and cloud platforms (Azure, AWS, or GCP).
  </li>
  <li>
   Strong analytical, debugging, and problem-solving skills.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Preferred Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experience with GraphRAG architectures.
  </li>
  <li>
   Knowledge of AI agent frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, or OpenAI Agents SDK.
  </li>
  <li>
   Experience with Model Context Protocol (MCP).
  </li>
  <li>
   Prompt engineering and AI evaluation frameworks.
  </li>
  <li>
   Knowledge of semantic search and hybrid retrieval.
  </li>
  <li>
   Experience with FastAPI, Django, or Flask.
  </li>
  <li>
   Familiarity with Kubernetes, CI/CD pipelines, and microservices.
  </li>
  <li>
   Experience building knowledge graphs and ontology design.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 What We Offer
 <br/>
 <br/>
 <ul>
  <li>
   Opportunity to build cutting-edge AI products.
  </li>
  <li>
   Collaborative and innovative engineering environment.
  </li>
  <li>
   Exposure to the latest AI technologies and frameworks.
  </li>
  <li>
   Professional growth and continuous learning opportunities.
  </li>
  <li>
   Competitive salary and benefits package.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 Join Our Team
 <br/>
 <br/>
 If you're passionate about building practical AI applications, enjoy working with the latest AI technologies, and thrive in an AI-first development environment, we'd love to hear from you!
</div>


Applied AI Engineer (AI-First / Vibe Coding)

Jadeer

<div><h2 class="jobSectionHeader"><b>About the Role</b></h2><p>
We are looking for an <b>Applied AI Engineer</b> to design, build, and deploy intelligent AI solutions that solve real business challenges. In this role, you'll work with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), GraphRAG, AI agents, and knowledge graphs to create scalable, production-ready AI applications.</p><p>
This is an <b>AI-first engineering role</b>, where leveraging AI development tools such as ChatGPT, Cursor, GitHub Copilot, Claude, or Windsurf is an essential part of the development workflow.</p><h2 class="jobSectionHeader"><b>
Key Responsibilities</b></h2><ul><li><p>
Design, develop, and deploy AI-powered applications using LLMs.</p></li><li><p>
Build and optimize RAG and GraphRAG pipelines.</p></li><li><p>
Develop AI agents and multi-agent workflows for business automation.</p></li><li><p>
Design and manage knowledge graphs using GraphDB technologies.</p></li><li><p>
Integrate enterprise data sources with AI applications.</p></li><li><p>
Engineer prompts, workflows, and agent orchestration for reliable AI systems.</p></li><li><p>
Evaluate and optimize AI models for quality, latency, scalability, and cost.</p></li><li><p>
Build production-ready APIs and AI services.</p></li><li><p>
Collaborate with cross-functional teams to deliver AI-driven products.</p></li><li><p>
Stay up to date with the latest AI models, frameworks, and best practices.</p></li></ul><h2 class="jobSectionHeader"><b>
Requirements</b></h2><ul><li><p>
Bachelor's degree in Computer Science, Software Engineering, AI, or a related field.</p></li><li><p>
3+ years of experience developing AI-powered or data-intensive applications.</p></li><li><p>
Strong proficiency in Python.</p></li><li><p>
Hands-on experience with LLMs (OpenAI, Azure OpenAI, Anthropic, Gemini, or similar).</p></li><li><p>
Experience implementing Retrieval-Augmented Generation (RAG).</p></li><li><p>
Experience with Graph Databases such as Neo4j, Amazon Neptune, Memgraph, or GraphDB.</p></li><li><p>
Familiarity with vector databases such as Pinecone, Qdrant, Weaviate, Milvus, or pgvector.</p></li><li><p>
Experience integrating AI models through APIs and SDKs.</p></li><li><p>
Solid understanding of REST APIs, Git, Docker, and cloud platforms (Azure, AWS, or GCP).</p></li><li><p>
Strong analytical, debugging, and problem-solving skills.</p></li></ul><h2 class="jobSectionHeader"><b>
Preferred Qualifications</b></h2><ul><li><p>
Experience with GraphRAG architectures.</p></li><li><p>
Knowledge of AI agent frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, or OpenAI Agents SDK.</p></li><li><p>
Experience with Model Context Protocol (MCP).</p></li><li><p>
Prompt engineering and AI evaluation frameworks.</p></li><li><p>
Knowledge of semantic search and hybrid retrieval.</p></li><li><p>
Experience with FastAPI, Django, or Flask.</p></li><li><p>
Familiarity with Kubernetes, CI/CD pipelines, and microservices.</p></li><li><p>
Experience building knowledge graphs and ontology design.</p></li></ul><h2 class="jobSectionHeader"><b>
What We Offer</b></h2><ul><li><p>
Opportunity to build cutting-edge AI products.</p></li><li><p>
Collaborative and innovative engineering environment.</p></li><li><p>
Exposure to the latest AI technologies and frameworks.</p></li><li><p>
Professional growth and continuous learning opportunities.</p></li><li><p>
Competitive salary and benefits package.</p></li></ul><h2 class="jobSectionHeader"><b>
Join Our Team</b></h2><p>
If you're passionate about building practical AI applications, enjoy working with the latest AI technologies, and thrive in an AI-first development environment, we'd love to hear from you!</p></div>

FRONT

<div><p>Front is the customer operations platform built for B2B complexity, keeping every team, tool, and customer conversation in sync so companies can scale without losing connection. Others handle simple interactions. Front handles the coordination and context behind complex B2B customer relationships. Over 9,000 companies, including Uber Freight, Navan, and Stripe, rely on Front because it's the only one that can run the operational layer that makes customer-facing work actually succeed.</p><p></p><p>
Backed by Sequoia Capital and Salesforce Ventures, Front has raised $204M from leading venture capital firms and independent investors including top executives at Atlassian, Okta, Qualtrics, Zoom, and PagerDuty. Front has received numerous Great Place to Work accolades, including <b>Built In's 100 Best Midsize Places to Work in SF 2025</b>, <b>Top Places to Work by USA Today 2025</b>, <b>Y Combinator's list of Top Companies in 2023</b>, <b>#4 on Fortune&rsquo;s Best Workplaces in the Bay Area</b> ,<b>Inc. Magazine's 2022 Best Workplaces list</b>, and <b>Forbes Best Startup Employers 2022 List</b>.</p><p></p><p>
AI is transforming customer support and, with over 12 years of experience building customer operations solutions, Front is in a unique position to shape this transformation. The Core AI team at Front leverages AI to build functionality across the entire breadth of the product. Our workflow automations, agent assistance and operational insights have only scratched the surface, and user engagement is already extremely promising. This role would have the opportunity to get in at the ground floor and significantly influence the direction of the product as we scale.</p><p></p><p><b>
What will you be doing?</b></p><ul><li><p>
Design, develop, and deploy generative AI applications using NodeJS &amp; TS that enhance product features and user experiences, focusing on agentic applications to automate resolving user inquiries.</p></li><li><p>
Collaborate with product teams to identify opportunities for applying generative AI to solve user needs and improve the platform's capabilities.</p></li><li><p>
Lead the exploration and implementation of state-of-the-art generative AI techniques, ensuring Front stays ahead of technological trends.</p></li><li><p>
Inform on AI model training and deployment infrastructure, ensuring scalability and efficiency.</p></li><li><p>
Dive deep into real-world data, ensuring high-quality model training and iteration</p></li><li><p>
Monitor and evaluate the performance of AI applications, making adjustments and improvements to ensure they meet our high standards.</p></li><li><p>
Keep abreast of the latest developments in machine learning and AI, advocating for best practices and integrating new technologies where appropriate.</p></li></ul><p></p><p><b>
What skills and experience do you need?</b></p><p>
Must Have:</p><ul><li><p>
5+ years of experience in software development, with a strong focus on AI and machine learning projects.</p></li><li><p>
Demonstrable expertise in developing production applications using LLMs and Generative AI models, and familiarity with their underlying technologies.</p></li><li><p>
Strong experience with agentic methodologies, prompting techniques, RAG pipelines, evaluation mechanisms and fine-tuning LLMs preferred.</p></li><li><p>
High learning agility - you&rsquo;re excited when you encounter a problem you haven&rsquo;t seen before.</p></li><li><p>
Strong communication skills that illustrate a clear, structured thought process.</p></li></ul><p>
Should Have:</p><ul><li><p>
Excellent problem-solving abilities and the capacity to work both independently and as part of a team.</p></li><li><p>
Proficiency building production-grade web applications and demonstrated expertise in languages and concepts necessary to deliver these. Eg: Python, JS, TS, Database systems, etc.</p></li><li><p>
Strong communication skills, capable of explaining complex technical concepts to non-experts.</p></li><li><p>
Deep knowledge of algorithms, data structures, and principles of software engineering.</p></li></ul><p>
Nice to Have:</p><ul><li><p>
Knowledge in specialized machine learning areas (deep learning, reinforcement learning).</p></li><li><p>
Experience in SaaS or multiplayer application machine learning implementations.</p></li></ul><p></p><p><b>
Front operates on a hybrid model &mdash; we come together in the office each Tuesday, Wednesday, and Thursday to collaborate and stay connected.</b></p><p></p><p><b>
What we offer</b></p><ul><li><p>
Competitive salary</p></li><li><p>
Equity (we are post-series D &amp; backed by some of the best VCs in the US)</p></li><li><p>
Private health insurance, including plan options at no cost to employees</p></li><li><p>
Paid parental leave</p></li><li><p>
Flexible time off policy</p></li><li><p>
Flexibility to work from home Monday and Friday, unless posted as a fully remote role</p></li><li><p>
Mental health support with Workplace Options</p></li><li><p>
Family planning support with Maven</p></li><li><p>
$100 per month Lifestyle Stipend to spend on fitness, health and wellness, and other activities</p></li><li><p>
Wellness Days - Fronteers get an additional day off on months with no holidays</p></li><li><p>
Winter Break - Our offices are closed from Christmas to New Year's Day!</p></li></ul><p><i>
Front provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age or disability. By applying, you acknowledge and agree that you have read and understand the </i><i>California Recruiting Privacy Notice </i><i>&amp; </i><i>EU Privacy Notice</i></p><p>
Compensation Range: $205K - $238K</p></div>

Senior Applied AI Engineer

Ursa Space Systems

<div><h1 class="jobSectionHeader"><b>Applied AI/ML Engineer</b></h1><h2 class="jobSectionHeader"><b>
About the Role</b></h2><p>
Ursa Space turns complex satellite and spatial data into decision-ready answers. Our agentic GeoAI platform lets users ask a question in plain English about a place, an event, or an activity anywhere on Earth and handles the rest: selecting the right data sources, tasking sensors, running analytics, and delivering an insight report in minutes instead of hours.</p><p>
We're looking for an Applied AI/ML Engineer to help build the intelligence behind that platform. This is a hybrid role by design. Some weeks you'll be deep in computer vision training and deploying object detection and segmentation models on SAR and electro-optical satellite imagery. Other weeks you'll be building agentic systems: designing tool-calling workflows, orchestrating LLM-driven analysis pipelines, and building the evaluation infrastructure that keeps them reliable. The work varies significantly project to project, and the right candidate sees that as a feature, not a bug.</p><p>
You'll report to the Director of Analytics and work side-by-side with data scientists, image scientists, product owners, and customers. This role may include pre-scheduled on-call rotations requiring occasional evening or weekend technical support.</p><p>
This is a virtual role and an exempt position.</p><h2 class="jobSectionHeader"><b>
Job Summary</b></h2><ul><li>
Design, build, and maintain agentic AI systems that automate stages of the geospatial analysis cycle from natural-language question intake through data selection, multi-source analysis, and report generation</li><li>
Develop tool-use, orchestration, and context-management capabilities that connect LLMs to our geospatial data services, analytics, and 90+ integrated data feeds</li><li>
Conduct Verification and Validation (V&amp;V) against AI/ML and LLM outputs to ensure accurate resulting information</li><li>
Train, fine-tune, evaluate, and deploy computer vision models (object detection, segmentation, change detection) on SAR, EO, and other Earth Observation data</li><li>
Adapt and fine-tune vision-language models (VLMs) to move beyond bounding boxes toward full scene understanding and extracting the meaningful content of imagery, not just locating objects</li><li>
Build evaluation and observability infrastructure for both classical ML (precision/recall, IoU, AUC/ROC) and LLM/agent behavior (task success, groundedness, regression testing), and use it to drive measurable improvement</li><li>
Own projects end to end: from data definition and prototyping through production deployment, validation, and maintenance</li><li>
Work directly with product owners, internal platform users, and external customers to understand needs, translate requirements into agentic system designs, and explain how the technology works to people who experience it as a black box</li><li>
Integrate third-party and multi-source data sets into analysis pipelines</li><li>
Do ad-hoc analysis and answer time-sensitive questions from stakeholders across the organization</li><li>
Act as a technical resource for teammates to bring awareness of new models, techniques, and tools that help the whole team grow</li><li>
Owning measuring actual observed error against budget, not just believing the budget on paper.</li><li>
Adversarial and edge-case testing deliberately probing for failure modes (ambiguous imagery, conflicting sources, out-of-distribution inputs) rather than testing the happy path a developer already validated.</li><li>
Confidence calibration to ensure that a system's stated confidence actually corresponds to real-world correctness rates, which is its own measurement discipline.</li><li>
Experienced with traceability and reproducibility to demonstrate why the system produced a given output, on a specific input, at a specific model/data version.</li><li>
All other duties as assigned.</li></ul><h2 class="jobSectionHeader"><b>
Requirements</b></h2><ul><li>
B.S. or M.S. in Computer Science, Data Science, or a related STEM field</li><li>
4&ndash;6 years of experience building and deploying machine learning systems for product- or software-focused organizations</li><li>
Strong Python and production software engineering practices: Git, Docker, testing, code review, CI/CD</li><li>
Experience training and deploying deep learning models for computer vision tasks (object detection, image segmentation) using PyTorch or similar frameworks</li><li>
Hands-on experience building LLM-powered applications: prompt design, structured outputs, tool use / function calling, and agentic architectures</li><li>
Experience evaluating ML systems with appropriate metrics &mdash; both traditional (RMSE, FPR/TPR, AUC/ROC, IoU) and LLM/agent evaluation approaches</li><li>
Experience developing and deploying in AWS environments</li><li>
Strong communication skills: able to present findings and explain complex systems to technical and non-technical audiences, including customers</li></ul><h2 class="jobSectionHeader"><b>
Preferred Skills</b></h2><ul><li>
Prior experience with remote sensing data especially synthetic aperture radar (SAR), GIS, and/or spatial statistics</li><li>
Experience fine-tuning foundation models or VLMs (e.g., LoRA/PEFT, multimodal adaptation for domain-specific imagery)</li><li>
Familiarity with agent orchestration frameworks and protocols (e.g., LangGraph, Claude Agent SDK, MCP) and LLM observability/eval tooling</li><li>
Geospatial Python stack: GDAL, rasterio, geopandas, xarray</li><li>
Experience with SQL/NoSQL databases and vector stores</li><li>
Experience leading projects on complex, cross-discipline teams</li><li>
Familiarity with Confluence, Jira, and Miro</li><li>
Regression and drift detection: did a &quot;small&quot; model or prompt change silently degrade accuracy on a case type that isn't in the dev team's day-to-day test set?</li></ul><p><b>
Compensation</b></p><ul><li>
Ranges: $185,000 - $199,000.</li><li>
Compensation range includes base salary and is eligible for an annual bonus.</li><li>
New hires salaries are typically between the range minimum and the salary range midpoint. Actual placement in the range will depend on a candidate&rsquo;s job-related skills, experience, and expertise, as evaluated during the interview process.</li></ul><p><b><br>
Inclusion Statement</b></p><p>
We are dedicated to the belief that all lives have equal value. We strive for a global and cultural workplace that supports ever greater diversity, equity, and inclusion &mdash; of voices, ideas, and approaches &mdash; and we support this diversity through all our employment practices.</p><p>
All applicants and employees who are drawn to serve our mission will enjoy equality of opportunity and fair treatment without regard to race, color, age, religion, pregnancy, sex, sexual orientation, disability, gender identity, gender expression, national origin, genetic information, veteran status, marital status, and prior protected activity.</p><p><b>
Location</b></p>
<ul><li>We are headquartered in Ithaca, NY and have a remote workforce in other locations throughout the United States.</li>
</ul>
<p>Please note: applications without a relevant cover letter will not be considered. In your cover letter, we would like to hear your personal voice and learn about your sincere interest in Ursa Space Systems.</p>
<p></p><p><b>Benefits and Perks</b></p>
<ul><li>Competitive Compensation</li>
<li>Discretionary PTO &amp; Flexible Scheduling</li>
<li>Stock Options</li>
<li>401(k) Match</li>
<li>Medical, Dental and Vision Coverage for you and your dependents</li>
<li>FSA &amp; HSA Plans</li>
<li>Employer-paid Life Insurance</li>
<li>Employer-paid LTD and STD for Parental and Family Care</li>
<li>11 Paid Holidays</li>
<li>Employee Resource Groups</li>
<li>Educational Assistance Program</li>
<li>Professional Development Opportunities</li>
<li>And more&hellip;</li>
</ul>
<p></p><p><b>Company Values</b></p>
<ul><li>Use the team</li>
<li>Figure it out and own it</li>
<li>Aim for elegant simplicity</li>
<li>Empower diversity &amp; inclusivity</li>
<li>Do the right thing</li>
<li>Be scrappy</li>
</ul><p></p><p>XIocstDnR5</p></div>

Applied AI/ML Engineer

The Hartford

<div><h2 class="jobSectionHeader"><b>Job Details</b></h2>
<div><div><div>Location:</div>
<div>Hartford, CT</div>
</div><div><div>Category:</div><div>
Data &amp; Analytics</div>
</div><div><div>Employment Type:</div>
<div>Full time
</div></div><div><div>Job Ref:</div><div>
R2626256-168</div>
</div></div><p></p><div><div>Sr Data Engineer - GE07BE<p>
We&rsquo;re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals &ndash; and to help others accomplish theirs, too. Join our team as we help shape the future.<br>
</p><p></p><div><p>The Hartford is seeking a Senior AI Machine Learning Engineer within Employee Benefits Applied AI and Analytics (EB AIA) to help build, deploy, and sustain enterprise-scale predictive and applied AI solutions across pricing, underwriting, sales related EB business workflows. As a Senior AI/ML engineer you will manage and modernize the existing predictive model portfolio while helping the team expand into generative AI, agentic AI and other applied AI capabilities.</p></div><div><p>
The role is intended for a hands-on technical lead who can execute approved solution designs, deploy production-ready AI and ML components, operate reliable model pipelines, and guide junior engineers. The person should be able to translate architecture and design direction into working, governed, and production assets with minimal supervision.</p></div><div><p><b>
Team Description</b></p></div><div><p>
The Employee Benefits Applied AI and Analytics team provides insight, automation, and augmentation across the policy lifecycle for Employee Benefits customers and internal business stakeholders. EB AIA supports a portfolio that spans sales, pricing, underwriting, policy installation, renewal, service, and operational workflows.</p></div><div><p>
In addition to the existing portfolio of Predictive AI assets, the team is scaling an end-to-end AI-driven reimagination of EB underwriting and service organizations. The team partners closely with enterprise platform enablement team to apply consistent architecture and engineering practices while tailoring solutions for accuracy, transparency, scalability, and business usability.</p></div><div><p><b>
Primary Responsibilities</b></p></div><div><ul><li>Lead day-to-day engineering execution for the EB predictive model portfolio, including pricing and underwriting models, scoring pipelines, model refreshes, monitoring, data validations, and production support.</li></ul></div><div><ul><li>Build, deploy, and maintain AI/ML components and data pipelines that support applied AI use cases across pricing, underwriting, sales, service, renewal, and policy lifecycle workflows.</li></ul></div><div><ul><li>Implement approved solution designs from senior Applied AI Engineers, Architects, and Data Scientists; translate design patterns into tested, reliable production code and workflows.</li></ul></div><div><ul><li>Support the initial build-out of generative AI and agentic AI solutions, including prompt orchestration, retrieval-augmented generation patterns, evaluation workflows, guardrails, and integration with existing EB data and application ecosystems.</li></ul></div><div><ul><li>Develop and operate batch and near-real-time data/AI pipelines for model training, feature generation, inference, post-processing, business rules integration, and downstream consumption.</li></ul></div><div><ul><li>Deploy and sustain production AI services, jobs, APIs, and workflows in AWS and GCP environments using approved CI/CD, testing, observability, security, and operational practices.</li></ul></div><div><ul><li>Own implementation quality for assigned components, including code reviews, unit/integration testing, documentation, runbooks, production readiness checks, and incident response support.</li></ul></div><div><ul><li>Guide and mentor junior engineers by breaking down technical work, reviewing code, explaining model/data pipeline patterns, and ensuring consistent engineering practices.</li></ul></div><div><ul><li>Partner with Data Scientists, Data Engineers, Asset Owners, Underwriting, Pricing stakeholders to understand requirements, validate outputs, resolve data issues, and ensure model solutions fit business workflows.</li></ul></div><div><ul><li>Maintain model and pipeline governance artifacts, including lineage, model inputs/outputs, monitoring metrics, validation evidence, operational controls, and handoff documentation.</li></ul></div><div><ul><li>Identify risks, bottlenecks, and operational gaps in deployed AI/ML solutions and recommend practical improvements under the guidance of senior technical leadership.</li></ul></div><div><p><b>
Minimum</b><b> </b><b>Requirements</b></p></div><div><ul><li> Bachelor&rsquo;s degree in related field or 6+ years of equivalent experience in software engineering, data engineering, ML/DevOps engineering, applied AI engineering, or closely related technical roles.</li></ul></div><div><ul><li>Master's degree in computer science, engineering, information technology, MIS, data science, or related discipline preferred.</li></ul></div><div><ul><li>Strong hands-on expertise in Python, SQL, SDLC practices, Git-based development, automated testing, and production-grade code delivery.</li></ul></div><div><ul><li>Experience deploying and operating data, AI, or ML workloads in AWS and GCP, including cloud storage, managed compute, orchestration, IAM-aware access patterns, logging, and monitoring.</li></ul></div><div><ul><li>Experience with ML engineering concepts such as feature pipelines, model training workflows, batch scoring, inference services, model monitoring, drift detection, validation, retraining, and production support.</li></ul></div><div><ul><li>Ability to work within defined architecture, enterprise security standards, data governance expectations, coding standards, and operational controls.</li></ul></div><div><ul><li>Ability to lead implementation work, guide junior engineers, communicate tradeoffs, and manage multiple model/pipeline deliverables with limited day-to-day direction.</li></ul></div><div><p><b>
Preferred Experience</b></p></div><div><ul><li>Experience in insurance, employee benefits, pricing, underwriting, risk selection, sales enablement, or policy lifecycle analytics.</li></ul></div><div><ul><li>Experience supporting predictive model portfolios that require periodic refreshes, performance tracking, business validation, and governed production deployment.</li></ul></div><div><ul><li>Experience with generative AI or agentic AI implementation patterns, including RAG, prompt evaluation, LLM application integration, AI safety controls, human-in-the-loop workflows, and model output validation.</li></ul></div><div><ul><li>Experience with orchestration and workflow tools such as Airflow, Cloud Composer, Step Functions, Vertex AI Pipelines, or comparable enterprise platforms.</li></ul></div><div><ul><li>Experience with CI/CD, containers, APIs, infrastructure-as-code concepts, observability, and production incident management.</li></ul></div><div><p><b>
Success Profile</b></p></div><div><p>
A successful candidate will be a hands-on engineering lead who can take a generated or approved architecture, convert it into deployable assets, keep predictive AI models running reliably, and help the team move into applied AI delivery. The candidate should be comfortable doing implementation work across pricing and underwriting under senior supervision, while also raising the capability of junior engineers through practical technical guidance.</p><p><i>
This role will have a Hybrid work schedule, with the expectation of working in an office 3 days a week
</i></p><p><i>Candidates must be authorized to work in the US without company sponsorship. The company will not support the STEM OPT I-983 Training Plan endorsement for this position.</i></p></div><p><b>
Compensation</b></p><p>
The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford&rsquo;s total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is:</p>
$117,200 - $175,800<p>
Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age</p></div></div></div><p></p>

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