• Work at the intersection of Artificial Intelligence and Threat Research • Work closely with subject-matter experts in cybersecurity to understand analyst workflows and their security operations procedures • Post-train LLMs and agents — supervised fine-tuning and reinforcement learning (RLHF/RLAIF, PPO/GRPO/DPO, reward modeling) — to automate analyst procedures and improve reliability on real security tasks • Devise AI agents and combine them into increasingly complex workflows: planning and reasoning loops, tool and function calling, and retrieval and memory • Research new approaches to agentic planning, and prototype state-of-the-art methods from the literature • Establish objective criteria for benchmarking agentic systems — evals, LLM-as-judge pipelines, and trajectory-level metrics, with real statistical rigor • Optimize prompts and inference to get the most out of every model • Collaborate and coordinate across Engineering, Data Science, and Managed Services teams, and partner with engineers to take prototypes toward production • Keep track of developments in the field of Artificial Intelligence and help identify, define, and prioritize areas for research

• Diseñar y construir pipelines de datos que alimenten los flujos de entrenamiento e inferencia de ML. • Desarrollar, evaluar e iterar modelos de machine learning y estadísticos orientados a soluciones de negocio. • Gestionar el ciclo de vida completo del modelo: desarrollo, validación, despliegue y monitoreo. • Integrar herramientas de GenAI (LLMs, copilots, agentes) en el flujo de desarrollo diario para acelerar las entregas. • Desplegar modelos en entornos de producción garantizando confiabilidad, rendimiento y mantenimiento del sistema. • Colaborar con stakeholders para traducir problemas complejos de negocio en soluciones funcionales de ciencia de datos. • Documentar el trabajo con claridad suficiente para que pueda ser mantenido y extendido por el equipo.

Role Description Are you data-driven, technically minded, and eager to improve one of the biggest affordable solar programs in the United States? Then join our team as a Solar Data Intern! Your efforts will directly contribute to the launch of a high-profile program with state-wide impacts. In this part-time (15-20 hours/week, ideally between Monday and Thursday) role, you’ll: - Organize, clean, and validate essential datasets to ensure they map successfully from their former system into ours. - Identify trends, investigate discrepancies, and propose deliverables by cross-collaborating with various teams within Energy Solutions' largest program. - Share your progress with high-level staff, including Team Leads. This experience will grant you: - Real-world experience working on a multi-million-dollar solar program and with its clients. - Understanding of data quality and its impact. - Proficiency in checking data quality and accuracy. You will also gain or deepen: - Software know-how, especially Excel. - Insight into behind-the-scenes software development and databases. - Potential client-facing experience and presentation(s). Qualifications - Intermediate to advanced Microsoft Excel skills. - Currently enrolled full- or part-time in an undergraduate program as a second to fourth-year student or enrolled in a graduate program. - Currently enrolled in or previously completed coursework in data, computer science, or an engineering-related field of study. - Strong research, technical writing, and analytical skills. Requirements - At least 4 work hours of your workday must overlap with the standard 9:00 AM to 5:00 PM workday in Pacific Standard Time (PST). - The ability to attend meetings between 9:00 AM and 5:00 PM PST on your workdays is preferred. - Currently enrolled full- or part-time in an undergraduate program as a second to fourth-year student or enrolled in a graduate program. - A US Citizen or permanent resident. - Available to meet your weekly hours requirement between May and August for Summer and between September and November for Fall. - Motivated by the Energy Solutions’ mission to reduce carbon emissions with an equity lens. Benefits - Undergraduate student: $21/hr. - Graduate student: $24/hr. Application Process You may apply to up to 2 positions per cycle. To apply, please submit: - Your updated resume/CV. - 2 short essays that meet the criteria below: - Be original documents written by you. - Be between 250 and 500 words each. - Answer the following prompts: - Describe how you have overcome adversity and applied the lessons learned to your academic, professional, or personal life. - Describe how the Internship you apply for will enhance or help launch your career in an energy-related industry. - Your work sample must: - Be an original document written by you. - Be between 1 and 3 pages long, single or double spaced, not including sources. - Demonstrate your ability to communicate your thinking about an idea. Important Notes - Our Fall 2026 Internship opportunities close on June 26, 2026, at 5:00 PM PST. - We will not accept late applications or make exceptions regarding the criteria. - We reserve the right to close our applications before the deadline. - If you have questions, please reach out to internships@energy-solution.com .

Role Description We are seeking a highly motivated and experienced Senior Data Scientist to join our Data Platform team. In this role, you will contribute to the design, development, and deployment of machine learning models and advanced analytics solutions that power our products and drive meaningful business outcomes. You will work closely with our engineering and research teams, collaborating on innovative projects that leverage modern ML frameworks, robust data pipelines, and scalable cloud platforms. What You’ll Be Doing - The Day to Day - Design, develop, and validate machine learning models for a variety of prediction, classification, and optimization tasks. - Collaborate with data engineers, product teams, researchers, and clinical subject matter experts to source, clean, and transform large, complex datasets for modelling and analysis. - Conduct exploratory data analysis, feature engineering, model selection, and hyperparameter tuning using modern ML libraries. - Implement and evaluate statistical models, supervised/unsupervised algorithms, and time series forecasting methods. - Develop reproducible, well-documented code using Python and industry-standard ML frameworks (e.g., scikit-learn, XGBoost, LightGBM, PyTorch, TensorFlow). - Communicate findings and insights to both technical and non-technical stakeholders through clear visualizations and presentations. - Translate business problems into machine learning solutions and contribute to model operationalization strategies. - Stay current with advancements in machine learning, AI, and data science practices. Qualifications - 5-7 years of professional experience developing machine learning and data science solutions in production environments. - Strong proficiency in Python, including core data science libraries: pandas, numpy, scikit-learn, matplotlib, polars, etc. - Experience with ML model development, evaluation, and deployment workflows. - Experience with MLOps tools and practices. - Hands-on experience with SQL and working with large-scale relational datasets. - Solid understanding of statistical modelling, data mining, and algorithm development. - Experience working in cross-functional teams and translating business needs into technical solutions. - Excellent communication, problem-solving, and analytical skills. Requirements - Experience deploying ML models using Azure Machine Learning or other cloud-native ML platforms. - Familiarity with Snowflake for data access, feature storage, or model deployment integration. Benefits - Competitive health plans (medical, dental, & vision insurance) - PTO (starting at 20 days) & 12 company holidays - 401(k) with company match - Telemedicine service provided by ESO - Savings accounts (FSA, HSA, DCA) - Employee Assistance Program (EAP) - Annual health and wellness reimbursement - Peace of mind benefits such as life insurance, disability insurance, and worksite benefits - Paid parental leave, new child program, & flexible parental return-to-work options - Casual office environments and unlimited office snacks and drinks