Sr. Data Scientist- AI Model Development

NextGenEnergyJobs; Canada; Hybrid; CAD 120,000 - 160,000; Full time

Job summary

Esri is seeking an experienced ML engineer to design, train, and deploy transformer-based models using proprietary telemetry data. You will develop LoRA/QLoRA adapters and collaborate with DevOps for data ingestion and training infrastructure.

You will design evaluation frameworks, compare custom models with foundation-model adapters, and contribute to production-ready AI solutions within Esri's platform ecosystem.

Qualifications

• 5+ years of professional software development, ML engineering, or data science experience.
• Strong applied ML background and transformer knowledge.
• Experience fine-tuning language models with LoRA/QLoRA.

Responsibilities

• Drive design, development, experimentation, validation, and deployment of AI models from telemetry data.
• Develop and fine-tune LoRA/QLoRA adapters for language models.
• Collaborate with DevOps and telemetry teams for data ingestion and training infrastructure.
• Design evaluation frameworks measuring quality, calibration, throughput, latency, and cost.
• Compare custom models with foundation-model adapters and advise on deployment strategies.
• Build and maintain automated testing and regression for models and adapters
• Define and document adapter contracts: config, tokenizers, input schemas, output, deployment.
• Collaborate with Esri platform teams to deliver production-ready AI solutions.
• Define training, validation, and benchmarking datasets.
• Stay current on transformer architectures, fine-tuning techniques, and telemetry-based AI.
• Author design documents and experiment reports; mentor engineers and data scientists.
• Collaborate with researchers across Esri during AI lifecycle.
• Solve complex ML, predictive modeling, and UX optimization challenges.

Skills

Transformer architectures

LoRA/QLoRA

PyTorch

Adapter techniques

Telemetry ML

Communication

ArcGIS knowledge

Education

Bachelor's degree in CS/DS/Math

Master's degree in CS/DS/AI

Tools

ONNX Runtime

LlamaSharp

Model serving

Telemetry pipelines

Job description

Utilize your expertise in machine learning, transformer architectures, foundation models, and telemetry-driven AI to impact millions of ArcGIS users worldwide.

Key Responsibilities

• Drive the design, development, experimentation, validation, and deployment of AI models built from proprietary telemetry datasets, including both custom transformer architectures and foundation model adaptations
• Develop and fine-tune LoRA and QLoRA adapters for language models and sequence prediction systems
• Work closely with DevOps and telemetry platform teams responsible for data ingestion, processing, and training infrastructure
• Design and implement evaluation frameworks that measure model quality, calibration, throughput, latency, memory efficiency, and operational cost
• Conduct rigorous comparisons between custom-built models and foundation-model-based adapter solutions, providing recommendations on architecture and deployment strategy
• Build and maintain automated testing and regression frameworks for both base models and adapter-specific functionality
• Define and document adapter contracts, including model configuration requirements, tokenizer expectations, input schemas, output behavior, and deployment assumptions
• Collaborate with platform engineering, product management, UX, and MLOps teams to deliver production-ready AI solutions with clearly defined capabilities and performance targets
• Define training, validation, and benchmarking datasets to support model development and evaluation
• Stay current on state-of-the-art developments in transformer architectures, parameter-efficient fine-tuning techniques, model serving technologies, and telemetry-based predictive systems
• Author technical design documents, experiment reports, and best-practice guidance for model development and deployment
• Mentor software engineers, data scientists, and analysts on model training, fine-tuning methodologies, telemetry-driven machine learning, and AI research practices
• Collaborate with researchers and developers across Esri throughout the AI research and development lifecycle
• Solve and articulate complex technical challenges involving machine learning, predictive modeling, and user experience optimization

Requirements

• 5+ years of professional software development, machine learning engineering, or data science experience
• Strong applied machine learning background and deep understanding of modern transformer architectures
• Hands-on experience developing and training custom transformer-based models from scratch
• Demonstrated experience fine-tuning small and mid-sized language models using parameter-efficient methods such as LoRA and QLoRA
• Experience building next-item and next-N prediction systems using telemetry, event, behavioral, or sequence data
• Experience with PyTorch, Transformer architectures, Foundation models LoRA and QLoRA fine-tuning techniques Model evaluation and benchmarking methodologies
• Strong analytical problem-solving skills and experience conducting research-oriented development
• Excellent written and verbal communication skills
• Ability to communicate complex technical concepts to both engineering and product leadership audiences
• Bachelor’s degree in Computer Science, Data Science, Mathematics, Artificial Intelligence, or a related field
• Master’s degree or higher in Computer Science, Data Science, Mathematics, Artificial Intelligence, or a related field
• Experience with Esri ArcGIS products and geospatial technologies
• Experience with adapter composition techniques, including weighted adapter merging, adapter routing, and mixture-of-adapters architectures
• Experience with Sequence modeling and predictive analytics
• Experience with ONNX Runtime, LlamaSharp
• Experience deploying and serving machine learning models in large-scale production environments
• Experience optimizing models for constrained environments, including CPU-only, edge, or low-memory GPU deployments
• Familiarity with recommendation systems, ranking systems, and behavioral sequence modeling
• Experience with retrieval-augmented generation (RAG) and hybrid AI architectures
• Experience with graph databases, graph analytics platforms, and graph-based machine learning techniques
• Familiarity with large-scale AI inference systems with performance and cost optimization considerations
• #LI-AL1
• #LI-Onsite
• Esri’s competitive total rewards strategy includes industry-leading health and welfare benefits: medical, dental, vision, basic and supplemental life insurance for employees (and their families), 401(k) and profit-sharing programs, minimum accrual of 80 hours of vacation leave, twelve paid holidays throughout the calendar year, and opportunities for personal and professional growth. Base salary is one component of our total rewards strategy. Compensation decisions and the base range for this role take into account many factors including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs.
• A reasonable estimate of the base salary range is