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Lenovo

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 We are Lenovo. We do what we say. We own what we do. We WOW our customers.
 
 
 Lenovo is a US$83 billion revenue global technology powerhouse, ranked #153 in the Fortune Global 500, and serving millions of customers every day in 180 markets. Focused on a bold vision to deliver Smarter Technology for All, Lenovo has built on its success as the world&rsquo;s largest PC company with a full-stack portfolio of AI-enabled, AI-ready, and AI-optimized devices (PCs, workstations, smartphones, tablets), infrastructure (server, storage, edge, high performance computing and software defined infrastructure), software, solutions, and services. Lenovo&rsquo;s continued investment in world-changing innovation is building a more equitable, trustworthy, and smarter future for everyone, everywhere. Lenovo is listed on the Hong Kong stock exchange under Lenovo Group Limited (HKSE: 992) (ADR: LNVGY).
 
 
 This transformation together with Lenovo&rsquo;s world-changing innovation is building a more inclusive, trustworthy, and smarter future for everyone, everywhere. To find out more visit www.lenovo.com, and read about the latest news via our StoryHub.
 
 
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 Please Note: This role will be hybrid with 3 days/week in office in Chicago, IL*
 
 
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 LATC Overview
 
 
 
 The Lenovo AI Technology Center (LATC)&mdash;Lenovo&rsquo;s global AI Center of Excellence&mdash;is driving our transformation into an AI-first organization. We are assembling a world-class team of researchers, engineers, and innovators to position Lenovo and its customers at the forefront of the generational shift toward AI. Lenovo is one of the world&rsquo;s leading computing companies, delivering products across the entire technology spectrum, spanning wearables, smartphones (Motorola), laptops (ThinkPad, Yoga), PCs, workstations, servers, and services/solutions. This unmatched breadth gives us a unique canvas for AI innovation, including the ability to rapidly deploy cutting-edge foundation models and to enable flexible, hybrid-cloud, and agentic computing across our full product portfolio. To this end, we are building the next wave of AI core technologies and platforms that leverage and evolve with the fast-moving AI ecosystem, including novel model and agentic orchestration collaboration across mobile, edge, and cloud resources. This space is evolving fast and so are we. If you&rsquo;re ready to shape AI at a truly global scale, with products that touch every corner of life and work, there&rsquo;s no better time to join us. #LATC
 
 
 
 Job Summary
 
 
 
 Lenovo is seeking a technical lead who will own the full agentic stack &mdash; from LLM orchestration, tool use, memory, and production deployment.
 
 
 
 Responsibilities
 
 
 
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 Design and ship agentic LLM pipelines: multi-step reasoning, tool use, reflection loops, and long-horizon planning and memory
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 Build evaluation frameworks to measure agent reliability and safety across different tasks.
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 Build and maintain RAG systems, vector stores, and external tool integrations
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 Deploy and scale agent systems in production; translate relevant research into working systems
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 Be a technical lead, working closely with other AI engineers, ML scientists, and technical product managers to put pipelines in production
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 Keep abreast of the latest developments in AI ML, applying cutting-edge research and methodologies to your work
 
 
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 Required Qualifications
 
 
 
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 6 years of industry experience in ML or applied AI with strong hands-on LLM experience (prompting, fine-tuning, inference optimization)
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 Bachelor&rsquo;s degree in computer science, applied math, physics, or a related field
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 Experience with NLP
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 Fluent in Python and the modern ML stack (PyTorch, Hugging Face, vLLM or equivalent)
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 Proven experience with agentic frameworks (LangGraph, AutoGen, CrewAI, or custom) and tool-use patterns (function calling, MCP, structured outputs)
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 Solid grasp of RAG architecture, embedding models, and LLM evaluation methodology
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 Strong software engineering fundamentals (python and at least one other programming language).
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 Experience with Git, and Continuous Integration/Continuous Deployment (CI/CD)
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 Experience deploying ML models using containerization and container orchestration technologies such as Docker and Kubernetes
 
 
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 Preferred Requirements
 
 
 
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 PhD or Master's preferred
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 Experience with computer vision
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 Experience with Agile frameworks, such as Scrum and Kanban
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 Rust experience for performance-critical inference or runtime components
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 Ability to effectively communicate technical solutions to both technical and business audiences, both verbally and in writing
 
 
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 The base salary range budgeted for this position in Chicago is $200k - $250k. Individuals may also be considered for bonus and/or commission. Lenovo&rsquo;s various benefits can be found here: https://www.lenovobenefits.com/enrolling-in-benefits/why-join-lenovo/
 
 
 #LATC
 
 
 
 We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, religion, sexual orientation, gender identity, national origin, status as a veteran, and basis of disability or any federal, state, or local protected class.
 
</div>

Advisory AI Engineer

Fitch Group

Requisition ID: 50531
 Business Unit: Fitch Group
 Category: Information Technology
 
Location: 
Chicago, IL, US
 
Date Posted: Aug 31, 2026
 
Machine Learning Engineer, Associate Director – AI Innovation Teams
 
Fitch Ratings is seeking a Machine Learning Engineer to join our new AI Innovation teams in Chicago—a bold initiative building the AI-powered future of financial analysis. We're not fine-tuning existing models or optimizing yesterday's algorithms. We're architecting the next generation: sophisticated agentic AI systems, intelligent automation that thinks, and ML capabilities that will redefine how credit analysis happens and how global financial markets consume insights.
 
This is AI's moment at Fitch, and we're moving decisively. As a Lead ML Engineer, you'll be a technical champion driving this transformation—building breakthrough ML systems that others will study, mentoring engineers who will become tomorrow's AI leaders, and establishing patterns that will scale across the organization. You're joining at the perfect inflection point: early enough to architect foundational decisions, resourced enough to execute boldly.
 
We need ML technologists who see greenfield opportunities as fuel rather than fear—whether you're an ML architect ready to design intelligent systems from first principles, an AI engineering leader who translates research breakthroughs into production reality, or a seasoned practitioner who recognizes that this moment demands courage over caution. If you're motivated by "let's prove this is possible" rather than "we need more data before we decide," this is a high-impact role where you'll spend less time justifying AI's potential and more time realizing it—alongside exceptional engineers who share your conviction that we're building something significant.
 
This role is ideal for someone who wants to remain deeply hands-on while operating at a senior level. You will contribute technical expertise, influence decision-making through strong engineering judgment, and partner closely with engineering leaders, product teams, and fellow engineers to deliver innovative AI solutions at scale. This is a senior individual contributor role with no direct people management responsibilities
 
What We Offer: 
Ground-floor ML leadership with enterprise resources – Define the ML architecture, technical standards, and engineering practices for Fitch's AI future while having the compute, research budgets, and organizational backing that most AI startups would envy; mentor and coach fellow ML engineers while remaining deeply hands-on with the most challenging technical problems
 Build breakthrough ML systems that matter – Develop net-new generative AI platforms, multi-agent orchestration systems, and intelligent automation that will process billions in credit decisions; experiment with frontier models, novel architectures, and unconventional approaches; see your ML innovations directly impact how global financial markets operate
 Access to cutting-edge ML infrastructure and research – Work with the latest LLMs, fine-tune foundation models, leverage enterprise-scale GPU clusters, experiment with emerging frameworks before they're mainstream, and collaborate with academic ML researchers; substantial conference and training budgets to stay at the forefront of AI innovation
 Shape ML governance and standards for an organization – Establish the ML engineering practices, model governance frameworks, and AI integration patterns that will guide Fitch's AI transformation; your architectural decisions will influence how a global financial services leader approaches intelligent systems
 Real production impact with sophisticated ML challenges – Build ML systems that analysts and financial professionals actually use daily; solve hard problems at the intersection of NLP, document intelligence, reasoning systems, and production-scale deployment; measure your impact in both model performance and business outcomes
 Accelerated career trajectory in AI leadership – High visibility to C-suite executives making billion-dollar strategic decisions; clear advancement paths to Principal ML Architect or AI Research Lead roles; opportunity to establish yourself as a recognized voice in financial AI and earn a reputation that opens doors across the industry
 
We'll Count on You To: 
Build transformative ML systems from the ground up – Design and architect net-new generative AI solutions, agentic workflows, and intelligent platforms using advanced ML frameworks (PyTorch, etc.), large language models, and emerging AI technologies that fundamentally change how analysts work and how Fitch operates
 Drive breakthrough AI innovation and experimentation boldly – Lead exploration of generative AI, multi-agent systems, RAG architectures, model fine-tuning, prompt engineering, and other emerging ML technologies; create cutting-edge proofs-of-concept; evaluate what's transformative versus what's hype; and turn research into production-quality AI capabilities
 Define ML technical vision and architecture for the future – Shape architectural decisions for ML systems, establish ML engineering standards, drive technology and framework choices, and influence how Fitch approaches intelligent platforms and AI governance across the organization
 Lead through innovation, influence, and mentorship – Mentor and coach fellow ML engineers while partnering with product squads, business stakeholders, and cross-functional teams to translate ambitious AI ideas into elegant technical solutions; foster a culture of experimentation, continuous learning, and calculated risk-taking
 Champion ML excellence while moving fast – Balance innovation velocity with ML engineering best practices; implement robust CI/CD pipelines for ML systems; develop scalable APIs (FastAPI, etc.) for model deployment; solve novel technical challenges at the intersection of cutting-edge AI research and production systems; and build solutions that are both breakthrough and reliable
 Drive ML governance and operational excellence – Ensure adherence to AI/ML governance guidelines, monitor SLAs for AI solutions, optimize model performance and reliability, and translate complex ML concepts for both technical and non-technical audiences across distributed teams
 Shape team culture and technical direction – Help define how our AI innovation teams operate, what "good" looks like for ML engineering, and how we balance exploration with delivery; model the curiosity, boldness, and technical rigor needed to succeed in a greenfield ML innovation environment
 
What You Need to Have: 
Deep ML technical expertise – 12+ years of professional experience building production AI/ML systems, with strong proficiency in Python, ML algorithms (from classical techniques to deep learning), and modern ML frameworks; proven track record of delivering advanced generative AI and ML solutions
 ML architectural mastery and greenfield experience – Demonstrated experience designing scalable ML systems from scratch; deep understanding of ML system architecture, model deployment patterns, and the ability to make bold architectural decisions for AI platforms in ambiguous environments
 Advanced generative AI expertise – Extensive hands-on experience developing and integrating generative AI solutions, working with large language models, building agentic systems, implementing RAG architectures, and training/fine-tuning neural networks using frameworks like PyTorch
 Bachelor's degree in Machine Learning, Computer Science, Data Science, Applied Mathematics, or related field
 Production ML engineering excellence – Deep understanding of ML operations, including containerization (Docker, Kubernetes/AWS EKS), cloud platforms (AWS/Azure), workflow orchestration (Airflow), automated testing for ML systems, and API development for model deployment
 Technical leadership and influence – Track record of mentoring and coaching engineers, driving ML initiatives in fast-moving environments, leading through technical excellence and influence rather than authority, and building credibility through results and vision
 Innovation and experimentation mindset – Demonstrated history of exploring emerging ML technologies, building AI proofs-of-concept, learning from failures, and translating cutting-edge research into production systems; comfort with ambiguity and rapid technological change
 Outstanding collaboration and communication – Ability to articulate ML technical vision to diverse audiences, work effectively with product squads and business partners, translate complex AI/ML concepts for non-technical stakeholders, and bring your whole self while remaining open to others' perspectives
 
What Would Make You Stand Out: 
Cutting-edge AI research to production experience – Track record of taking breakthrough AI capabilities from research/prototype to production-scale deployment; experience supporting seamless transitions from experimentation to enterprise-grade ML systems with real users
 ML thought leadership and technical strategy – History of establishing technical direction for ML initiatives, contributing to open-source ML projects, speaking at AI/ML conferences, publishing research, or writing about practical applications of emerging AI technologies
 Multi-agent and agentic systems expertise – Hands-on experience building multi-agent systems, agentic workflows, tool-using AI systems, or complex AI orchestration platforms that go beyond simple LLM integrations
 Advanced cloud-native ML infrastructure – Deep expertise building sophisticated ML infrastructure, MLOps pipelines, model serving platforms, and cloud-native AI systems at scale; experience optimizing cost and performance of production LLM deployments
 Financial services or analytical domain knowledge – Understanding of analytical workflows, credit analysis processes, regulatory requirements, financial data products, or how ML enables better financial decision-making; familiarity with credit ratings agencies is a significant advantage
 Startup or innovation team experience – History of building greenfield ML products, working in fast-paced AI innovation environments, or being part of 0-to-1 ML initiatives within larger organizations where you shaped technical direction
 Toronto AI/ML community connection – Active participation in Toronto's AI/ML research or engineering communities, connections to academic ML research groups, or strong interest in being part of Toronto's world-class AI ecosystem
 
If you're ready to build transformative ML systems with organizational backing, talented colleagues, and the resources to succeed—this is the moment to join us.
 
Why Fitch?
 
At Fitch Group, the combined power of our global perspectives is what differentiates us. Our global network of colleagues comes together to accomplish things greater than they ever could alone.
 
Every team member is essential to our business, and each perspective is critical to our success. We embrace a diverse culture that encourages a free exchange of ideas, guaranteeing your voice will be heard and your work will have an impact, regardless of seniority.
 
We are building incredible things at Fitch and we invite you to join us on our journey.
 
About Fitch Group
 
Fitch Group is a global leader in financial information services with operations in more than 30 countries. Wholly owned by the Hearst Corporation, we are comprised of three main businesses: Fitch Ratings | Fitch Solutions | Fitch Learning.
 
For more information please visit our websites: www.fitchratings.com | www.fitchsolutions.com | www.fitchlearning.com
 
Fitch is committed to providing global securities markets with objective, timely, independent and forward-looking credit opinions. To protect Fitch's credibility and reputation, our employees must take every precaution to avoid conflicts of interests or any appearance of a conflict of interest. Should you be successful in the recruitment process at Fitch Ratings you will be asked to declare any securities holdings and other potential conflicts prior to commencing employment. If you, or your immediate family, have any holdings that may conflict with your work responsibilities, you may be asked to divest yourself of them before beginning work.
 
Fitch Group is proud to be an Equal Opportunity and Affirmative Action Employer. We evaluate qualified applicants without regard to race, color, national origin, religion, sex, sexual orientation, gender identity, disability, protected veteran status, and other statuses protected by law.
 
FOR CHICAGO ROLES ONLY: Expected base pay rates for the role will be between 140,000 CAD and 175,000 USD. Actual salaries will be determined on an individualized basis and may vary based on factors including but not limited to education, training, experience, past performance, and other job-related factors. Base pay is one part of Fitch’s total compensation package, which, depending on the position, may also include commission earnings, discretionary bonuses, long-term incentives, and other benefits sponsored by Fitch.
 
#LI-Group
 
#LI-AT
 
#LI-Hybrid

Machine Learning Engineer, Associate Director (Chicago)

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Advisory AI Engineer

Machine Learning Engineer, Associate Director (Chicago)