Your Title: Senior AI Engineer
Job Location: Mexicali, Mexico
Our Business Segment: Architecture, Engineering, Construction and Owner Segment (AECO)
What if your expertise could redefine the future of construction, one intelligent algorithm at a time?
This senior technical leadership role is for an individual recognized as a technical authority in AI/ML, capable of influencing organizational strategy and driving significant business impact. The successful candidate will lead complex initiatives, solve highly unique problems, and mentor other engineers, while shaping the future direction of AI/ML capabilities at Trimble. This position demands a blend of deep technical expertise, strategic foresight, and exceptional communication skills to navigate complex technical and business landscapes.
What You Will Do
Lead the identification, training, and refinement of advanced deep learning models to solve highly complex, real-world problems at scale, contributing significantly to organizational functional strategy related to AI/ML.
Strategically curate and maintain effective datasets, driving data coverage and quality initiatives for critical industry use cases across the organization.
Work closely with cross-functional teams and domain experts, translating ambiguous, high-level needs into clear and actionable ML tasks that align with business objectives.
Drive and define MLOps best practices across teams, including advanced containerization strategies, robust model versioning, and sophisticated monitoring systems, ensuring proactive problem resolution when models encounter issues.
Maintain an expert-level awareness of the frontier of machine learning research, including foundation models and self-supervised methods, and strategically adapt breakthroughs to production code with broad business impact.
Architect and build advanced AI agents capable of complex reasoning, external tool use, and self-improvement through reflection loops, ensuring they deliver significant real-world value and strategic advantage.
Design, implement, and maintain rigorous benchmarks to evaluate AI agent behaviors, robustness, and alignment.
Optimize complex ML models and agents for extreme performance, scalability, and cost-efficiency, adeptly balancing accuracy with practical resource constraints and long-term sustainability.
Serve as a technical expert and thought leader within the field, influencing internal and external stakeholders, including senior management, on advanced technical issues and strategic directions.
Apply deep learning technologies to confer advanced capabilities to systems, adapting ML to cutting-edge areas such as virtual reality, augmented reality, artificial intelligence, and robotics, pushing the boundaries of what is possible.
Drive initiatives related to automated invoicing, payroll, and bank reconciliation through AI-driven financial analysis and auditing.
What Skills & Experience You Should Bring
Master's or Ph.D. in Computer Science, Math, Engineering, Statistics, or a related quantitative field with 7+ years of progressively responsible and relevant experience, demonstrating expert-level proficiency.
Specialized depth and/or breadth of expertise in machine learning and deep learning, coupled with broad knowledge of related job families within the engineering group.
Proven track record as a Principal or Lead Machine Learning Engineer, or similar expert-level role, with extensive evidence of production-ready ML work, including significant shipped projects, impactful open-source contributions, or a robust GitHub portfolio demonstrating innovative solutions.
Expert-level fluency in Python and deep learning frameworks (PyTorch is a must, TensorFlow is welcome), along with deep expertise in scientific computing libraries (NumPy, pandas, scikit-learn).
Extensive experience with Linux and bash scripting in production environments.
Solid grounding and proven expertise in data structures, advanced data modeling, and complex software architecture, with the ability to design and oversee large-scale, maintainable codebases.
Exceptional practical statistical sense, with a proven ability to design and conduct rigorous experiments, analyze and interpret results critically, and avoid common pitfalls like biased sampling or flawed metrics in complex scenarios.
Superior algorithmic and problem-solving skills, capable of tackling unique and highly complex challenges with structured, innovative approaches, and a track record of refining solutions under ambiguity.
Proven ability to lead others to solve highly complex problems, working independently and providing guidance in only the most intricate situations.
Exceptional communication skills, capable of articulating complex ideas, anticipating potential objections, and persuasively influencing others, often at senior executive levels.
Deep expertise in generative AI models (e.g., LLMs, diffusion models) and their practical applications, including fine-tuning, prompt engineering, and understanding of underlying architectures (e.g., Semantic Kernel).
Experience with Responsible AI principles, including fairness, interpretability, and transparency, in model development and deployment.
Expertise in MLOps, AIOps, and integrating AI into DevOps pipelines for automation, security, and compliance (e.g., Azure DevOps, New Relic, Azure Monitor).
Extensive experience with computer vision techniques for image/drawing analysis (e.g., Title Block Extraction, Symbol Extraction and Classification, 360 video processing).
Experience with vector search technologies (e.g., MongoDB Atlas Search).
What Skills & Experience You Could Bring
- Recognized as a technical expert or "guru" within the AI/ML field, with a demonstrated capacity for external thought leadership and industry contributions.
- A proven track record of directly impacting business direction through the development of innovative services or products powered by AI/ML.
- Significant experience influencing product, process, or service improvements based on deep technical and business understanding, translating technical vision into tangible business value.
- Contributions to patents, industry standards, or significant academic publications, reflecting a commitment to advancing the field.
- Highly adaptable and curious, consistently digging into and strategically adopting new techniques or tools to drive innovation and competitive advantage.
- Experience with cloud-native MLOps platforms (e.g., AWS SageMaker, Azure ML, Google Cloud Vertex AI) for managing the end-to-end ML lifecycle.
About Trimble Mexico
Trimble is expanding in Mexico by setting up a world-class software research & development center to accelerate the delivery of products and services worldwide. Become one of the pioneers that helps set the bar of excellence and culture that will shape our future.
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