Role Description You'll work on the C++ layer that powers local AI, porting and enhancing inference engines like llama.cpp or similar, to run efficiently on edge devices. Your focus is on the runtime: making models load faster, run leaner, and perform well across different hardware. You'll ensure that the inference layer is stable, optimized, and ready for integration with the rest of the stack. This role is for engineers who want to work close to the metal, enabling private and fast on-device AI without relying on cloud infrastructure. Responsibilities - Work on deploying machine learning models to edge devices using the frameworks: llama.cpp, ggml - Collaborate closely with researchers to assist in coding, training and transitioning models from research to production environments - Integrate AI features into existing products, enriching them with the latest advancements in machine learning - Excellent programming skills in C++, experience in Javascript is a bonus - Strong experience with Llama.cpp and ggml inference engines, which facilitates the deployment of models to specific GPU architectures - Good understanding of deep learning concepts and model architectures - Experience with transformers, LLMs, Diffusion models - Demonstrated ability to rapidly assimilate new technologies and techniques - A degree in Computer Science, AI, Machine Learning, or a related field, complemented by a solid track record in AI R&D Benefits - Remote flexibility: Work where and how you work best - we trust you to deliver - Fair compensation: Competitive salary + benefits that matter (medical, learning) - Ownership opportunities: See a problem worth solving? Own it. We back smart risks over bureaucratic safety - AI enhancement: We leverage AI to make you faster and stronger - complementing your abilities, not replacing them - Learning investment: English classes, professional development - Career progression: Real paths up, not just sideways shuffling - Responsive teammates: No ignored Slacks, no "not my problem" attitudes - Supportive culture: When you're stuck, people help. When things break, we fix them together - Human connections: Regular meetups, tech talks, and actual relationships beyond work

Role Description You'll work on the C++ layer that powers local AI, porting and enhancing inference engines like llama.cpp or similar, to run efficiently on edge devices. Your focus is on the runtime: making models load faster, run leaner, and perform well across different hardware. You'll ensure that the inference layer is stable, optimized, and ready for integration with the rest of the stack. This role is for engineers who want to work close to the metal, enabling private and fast on-device AI without relying on cloud infrastructure. Responsibilities - Work on deploying machine learning models to edge devices using the frameworks: llama.cpp, ggml - Collaborate closely with researchers to assist in coding, training and transitioning models from research to production environments - Integrate AI features into existing products, enriching them with the latest advancements in machine learning - Excellent programming skills in C++, experience in Javascript is a bonus - Strong experience with Llama.cpp and ggml inference engines, which facilitates the deployment of models to specific GPU architectures - Good understanding of deep learning concepts and model architectures - Experience with transformers, LLMs, Diffusion models - Demonstrated ability to rapidly assimilate new technologies and techniques - A degree in Computer Science, AI, Machine Learning, or a related field, complemented by a solid track record in AI R&D Qualifications - Excellent programming skills in C++ - Experience in Javascript is a bonus - Strong experience with Llama.cpp and ggml inference engines - Good understanding of deep learning concepts and model architectures - Experience with transformers, LLMs, Diffusion models - A degree in Computer Science, AI, Machine Learning, or a related field Requirements - Demonstrated ability to rapidly assimilate new technologies and techniques Benefits - Remote flexibility: Work where and how you work best - we trust you to deliver - Fair compensation: Competitive salary + benefits that matter (medical, learning) - Ownership opportunities: See a problem worth solving? Own it. We back smart risks over bureaucratic safety - AI enhancement: We leverage AI to make you faster and stronger - complementing your abilities, not replacing them - Learning investment: English classes, professional development - Career progression: Real paths up, not just sideways shuffling - Responsive teammates: No ignored Slacks, no "not my problem" attitudes - Supportive culture: When you're stuck, people help. When things break, we fix them together - Human connections: Regular meetups, tech talks, and actual relationships beyond work

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven decision making. You will work on developing predictive models, conducting statistical analysis, and creating data visualisations to solve complex business problems. Focused on relationships, you are building meaningful client connections, and learning how to manage and inspire others. Navigating increasingly complex situations, you are growing your personal brand, deepening technical expertise and awareness of your strengths. You are expected to anticipate the needs of your teams and clients, and to deliver quality. Embracing increased ambiguity, you are comfortable when the path forward isn't clear, you ask questions, and you use these moments as opportunities to grow. Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to: Respond effectively to the diverse perspectives, needs, and feelings of others. Use a broad range of tools, methodologies and techniques to generate new ideas and solve problems. Use critical thinking to break down complex concepts. Understand the broader objectives of your project or role and how your work fits into the overall strategy. Develop a deeper understanding of the business context and how it is changing. Use reflection to develop self awareness, enhance strengths and address development areas. Interpret data to inform insights and recommendations. Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements. The Opportunity As part of the People Tech & AI team you will develop, test, and validate Generative AI agents and data pipelines, promoting reliability, scalability, and alignment with PwC standards. As a Senior Associate you will analyze complex problems, mentor others, and maintain elevated standards while collaborating with multidisciplinary teams to support AI-enabled client solutions. This position provides an exciting opportunity to enhance your skills in automated testing and governance controls while contributing to innovative AI-driven solutions. Responsibilities - Apply automated testing and governance controls effectively - Analyze complex issues and provide actionable insights - Mentor and guide junior associates in their tasks - Uphold rigorous standards of quality and technical excellence What You Must Have - Bachelor's Degree in Computer Science, Data Processing/Analytics/Science - At least 2 years of experience in data engineering, AI/ML engineering, or quality engineering - In lieu of a Bachelor's Degree, demonstrating, in addition to the minimum years of experience required for the role, three years of specialized training and/or progressively responsible work experience in technology for each missing year of college What Sets You Apart - Demonstrating three years of specialized training in technology preferred - Experience with test automation and CI/CD pipelines - Familiarity with LLMs and prompt engineering concepts - Understanding enterprise data patterns and quality frameworks - Building and maintaining automated test suites for AI agents - Validating integrations with Power Automate platform - Executing LLM evaluation frameworks using defined metrics - Working with data scientists and ML engineers - Upholding professional standards and documentation expectations The salary range for this position is: $55,000 - $151,470. For residents of Washington state the salary range for this position is: $55,000 - $187,000. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glance As PwC is an equal opportunity employer, all qualified applicants will receive consideration for employment at PwC without regard to race; color; religion; national origin; sex (including pregnancy, sexual orientation, and gender identity); age; disability; genetic information (including family medical history); veteran, marital, or citizenship status; or, any other status protected by law. PwC does not intend to hire experienced or entry level job seekers who will need, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth within the following policy: https://pwc.to/H-1B-Lottery-Policy. Learn more about how we work: https://pwc.to/how-we-work For only those qualified applicants that are impacted by the Los Angeles County Fair Chance Ordinance for Employers, the Los Angeles' Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, San Diego County Fair Chance Ordinance, and the California Fair Chance Act, where applicable, arrest or conviction records will be considered for Employment in accordance with these laws. At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship to responsibilities such as accessing sensitive company or customer information, handling proprietary assets, or collaborating closely with team members. We evaluate these factors thoughtfully to establish a secure and trusted workplace for all. Applications will be accepted until the position is filled or the posting is removed, unless otherwise set forth on the following webpage. Please visit this link for information about anticipated application deadlines: https://pwc.to/us-application-deadlines #LI-Remote #LI-Hybrid #BI-Hybrid

Role Description We're hiring a Staff AI/ML Engineer to help build the AI at the core of Burq — and we mean core, not cosmetic. We're pushing to be at the forefront of AI in logistics: building intelligent agents that automate work the industry still does by hand, and the prediction and optimization models that power smarter operational decisions in real time. This is a high-ownership, hands-on role that spans two connected layers: - The agentic layer: multi-agent systems and copilots that understand a request and execute the right workflow end to end, automating manual operational work. - The intelligence layer: forecasting, prediction, and optimization models that make and improve the decisions behind the product, getting smarter with every outcome. You'll take ambiguous AI ideas from prototype to production, set the bar for what reliable AI looks like in an operationally demanding domain, and help define what the AI-native version of Burq becomes. You'll work closely with the founders, product, and engineering, with a high impact on the most important technical work in the company. What You'll Do - Design and ship production AI systems — multi-agent orchestration, routing, and specialized agents that take a request and carry it through to a reliable outcome. - Automate manual operational work across onboarding, support, exceptions, and document/data understanding — turning processes that take hours or days into seconds. - Build the models behind the decisions — forecasting, prediction, matching/allocation, optimization, and reliability scoring that ground the product in data instead of guesswork, exposed as services the agent layer can call. - Design the learning loop. Instrument decisions and their outcomes so models continuously improve, with the data and evaluation infrastructure to support it. - Own reliability and evaluation. Build the eval harnesses, tracing, observability, and guardrails for complex AI workflows where mistakes carry real operational and financial consequences — and prove a model or agent beats the status quo before it ships. - Make the build-vs-rules calls — know when a model genuinely wins, when an agent is the right tool, and when a simple rule is the smarter answer. - Raise the bar and help the team grow — push our prototyping-to-production pipeline forward and mentor engineers as the AI team scales. Qualifications - You've shipped production AI/ML, not just prototypes — and dealt with the real tradeoffs of edge cases, quality, latency, cost, and reliability. - You have real depth on at least one of these, and working fluency across both: - Generative / agentic AI — multi-agent orchestration, tool/function calling, RAG, structured outputs, and the modern stack (e.g., LangGraph/LangChain, MCP), across providers (Amazon Bedrock, Azure OpenAI, Anthropic, OpenAI). - Applied ML / decision intelligence — forecasting, optimization, matching/allocation, ranking, or prediction models that drive operational decisions with measurable business impact. - You design and trust your own evaluation — offline and online, tied to business outcomes, with safe rollout (e.g., shadow mode) and drift monitoring. - You're deeply hands-on and ship fast — strong in Python, modern API/services (e.g., FastAPI), and sound ML-systems and architecture instincts. - You've built for operationally complex or high-stakes environments where quality and reliability genuinely matter. - You communicate clearly, make decisions quickly, and can lead technical work without needing heavy process. Bonus Points - Background in logistics, supply chain, transportation, marketplaces, mobility, or fulfillment. - Operations research / optimization, or reinforcement learning / bandits for sequential decision-making. - Multimodal / document understanding, computer-use, or browser automation. - Real-time / streaming systems, feature stores, and production MLOps at scale. - Patents or peer-reviewed publications, or experience as an early/founding engineer. Location This is a fully remote role, open to candidates based in the United States and Canada, with a few in-person offsites throughout the year. How We Work We're remote with a few in-person offsites throughout the year. We move quickly, default to writing, and ship early to real customers before rolling things out broadly. AI is part of how we work every day, not a separate initiative — we expect people to experiment with new tools, share what they learn, and continuously rethink how great products get built. We care more about speed, ownership, and iteration than process for the sake of process. Benefits - Competitive salary, stock options, and performance-based bonuses - Fully remote - Comprehensive medical, vision, and dental insurance Company Description At Burq, we value diversity. We are an equal opportunity employer: we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.