Role Description As part of Intersect’s Development Engineering team, you’ll help shape the engineering standards, technical governance, and innovation strategies that support some of the industry’s largest utility-scale solar, wind, and energy storage projects. This role serves as a technical leader responsible for developing and continuously improving engineering standards, specifications, processes, and contract exhibits that drive consistency, quality, and long-term value across Intersect’s portfolio. - Collaborate closely with Development Engineering, Procurement, Construction, Asset Management, Legal, Finance, EPC partners, consultants, and equipment suppliers. - Influence how projects are designed, contracted, built, and operated while helping Intersect scale efficiently and responsibly. Qualifications - Bachelor’s degree in Civil Engineering, Structural Engineering, or a related discipline; equivalent practical experience will also be considered. - 7+ years of technical civil and/or structural design experience, including 2+ years leading multidisciplinary design processes for utility-scale power projects. - Demonstrated success developing engineering standards, specifications, design criteria, governance frameworks, and continuous improvement programs across multiple projects or portfolios. - Strong understanding of design development, construction methods, applicable codes and standards, permitting considerations, technical risk management, and EPC contracting structures. - Strong project management, organizational, and stakeholder management skills. - Excellent written, verbal, and presentation communication skills. - Experience collaborating across engineering, procurement, construction, operations, and commercial functions. - Strategic thinking combined with strong attention to detail and a commitment to practical execution. - A collaborative leadership style that balances technical excellence, innovation, standardization, and business objectives. - Curiosity, adaptability, and a continuous improvement mindset that supports organizational growth and engineering excellence. Requirements - Lead the development and evolution of civil and structural engineering standards, specifications, design criteria, and best practices across Intersect’s project portfolio. - Drive standardization initiatives that improve quality, constructability, efficiency, and long-term project performance. - Integrate lessons learned from project execution into scalable engineering processes and governance frameworks. - Champion continuous improvement efforts that strengthen technical consistency and organizational effectiveness. - Improve engineering-related EPC contract exhibits, technical requirements, and supporting documentation to align with project objectives and portfolio learnings. - Partner with Engineering, Procurement, Construction, and Operations teams to strengthen technical risk management practices. - Support contracting strategies that improve project execution, consistency, and long-term value creation. - Provide technical expertise to help resolve complex engineering and commercial challenges. - Identify, evaluate, and advance emerging technologies, equipment solutions, and design approaches that improve project outcomes. - Lead technical due diligence efforts, pilot programs, and implementation strategies for new technologies and methodologies. - Monitor industry trends and assess opportunities to improve reliability, reduce costs, and accelerate project delivery. - Foster a culture of innovation by encouraging thoughtful evaluation and adoption of new engineering solutions. - Serve as a technical leader for civil and structural engineering standards, innovation initiatives, and continuous improvement programs across the organization. - Promote knowledge sharing and develop scalable engineering tools, templates, and processes. - Influence the adoption of best practices across development, design, construction, and operational teams. - Support portfolio growth through technical excellence, collaboration, and disciplined decision-making. Benefits - Compensation: $185,000 - $200,000 (total compensation includes base salary + bonus in USD) - Equity: Beyond your salary, you’ll receive an Equity Grant, giving you a meaningful stake in our parent company. - Health & wellness: 100% premium coverage for you and your dependents on medical, dental, and vision. - Time to recharge: Unlimited PTO, plus two company-wide breaks (Fourth of July & end of year). - Family support: Up to 12 weeks of fully paid parental leave, plus 6 additional weeks for birth parents; access to family planning and family care support through Carrot and Maven. - Mental health: Free access to Spring Health, including 5 free therapy and psychiatry sessions, plus a Headspace account for mindfulness and meditation through our physical health vendor, Wellhub+. - Perks & extras: $150 monthly food stipend, $150 monthly reimbursement for cell phone and internet, pet insurance allowance, full home office setup, free access to UrbanSitter with $625 in quarterly company-paid credits, ActiveHero, and One Medical.

Role Description We are looking for an LLM Fine-Tuning Engineer to design, execute, and operationalize fine-tuning workflows for large language models across supervised, preference-based, and reinforcement learning approaches. The role requires: - Deep practical experience with modern training stacks. - Careful dataset construction and rigorous evaluation methodology. - Engineering discipline to operate complex training pipelines reliably. - Strong ML intuition combined with production-grade engineering practices. - Ability to navigate trade-offs between data quality, compute budget, evaluation rigor, and shipping velocity. - Collaboration with cross-functional partners to translate ambiguous requirements into well-engineered solutions. - Raising the bar through code review, design review, and mentorship of junior engineers. - Strong engineering discipline, clear communication style, and a track record of shipping meaningful work that holds up well in production. Qualifications - Master’s or PhD in Computer Science, Machine Learning, or a related field; or equivalent experience. - Six or more years of combined ML research and engineering experience, with significant LLM exposure. - Strong proficiency in Python and modern deep learning frameworks, especially PyTorch. - Hands-on experience fine-tuning transformer-based language models at non-trivial scale. - Familiarity with distributed training strategies including FSDP, ZeRO, and pipeline parallelism. - Experience with RLHF, DPO, or other preference optimization techniques. - Strong understanding of evaluation methodology, benchmarks, and human evaluation design. - Experience operating training jobs on GPU clusters and recovering from failures. - Strong written and verbal communication skills. - Track record of shipping or publishing impactful LLM work. Requirements - Design and execute fine-tuning experiments for large language models using supervised, DPO, RLHF, and related techniques. - Lead dataset construction, curation, and quality assurance processes for instruction tuning and preference data. - Build scalable training pipelines on top of modern distributed training frameworks. - Tune hyperparameters, optimizer configurations, and training stability strategies for large-model fine-tuning. - Implement parameter-efficient fine-tuning techniques such as LoRA, QLoRA, and adapter-based methods. - Design rigorous evaluation suites including automated benchmarks, human evaluation, and capability-specific probes. - Implement safety, refusal, and policy evaluations to track model behavior across releases. - Operate large-scale training jobs on GPU clusters, diagnosing failures and recovering training state reliably. - Optimize training throughput using mixed precision, sequence packing, and efficient attention implementations. - Manage model artifacts, lineage tracking, and reproducibility across many concurrent experiments. - Collaborate with product, research, and platform teams to align fine-tuning roadmaps with business needs. - Document training methodology, results, and decisions clearly for technical and non-technical audiences. - Mentor engineers on fine-tuning best practices, evaluation rigor, and responsible deployment. - Stay current with LLM research and translate advances into production-ready fine-tuning recipes. Benefits - Competitive base salary commensurate with experience, plus benefits. - Long-term, multi-year engagement aligned to the Bright Vision SOW delivery roadmap. - 100% remote work opportunity.

• Lead the technical definition and evolution of the Data Lake strategy, ensuring a robust and scalable architecture; • Design and structure data layers (Raw, Trusted, Refined) and processing flows based on ETL and ELT patterns; • Establish guidelines so the architecture supports the company’s growth in volume and complexity; • Develop and automate complex data pipelines, ensuring efficient delivery for predictive models and advanced analytics; • Continuously optimize the performance of data flows, reducing latency and operational processing costs; • Implement tools and practices that enable scalable data modeling oriented to strategic decision-making; • Manage the data acquisition lifecycle, from ingestion through provisioning to stakeholders; • Ensure data quality, integrity and reliability by establishing monitoring and validation processes; • Act as a bridge between technology and the business areas, ensuring data solutions are aligned with the company’s strategic objectives.

• The Ingestion team develops a full-cycle data ETL pipeline and provides data to underlying stakeholders. • You would be responsible for end-to-end implementation of features, advocating for best practices, and providing technical leadership.