Opus 2

Machine Learning Engineer

• Design, build, and maintain MLOps infrastructure, establishing ML CI/CD best practices including model testing, versioning, and deployment.
• Develop and manage scalable automated pipelines for training, evaluating, and deploying ML models, with emphasis on LLM systems.
• Implement robust monitoring and logging for production models to track performance, drift, and data quality.
• Collaborate with Data Scientists to containerize and productionize models and algorithms, including RAG and Graph RAG approaches.
• Manage and optimize cloud infrastructure for ML workloads (e.g., Amazon Bedrock), focusing on performance, cost-effectiveness, and scalability.
• Automate provisioning of ML infrastructure using Infrastructure as Code.
• Integrate ML models into production product architecture, working closely with product and engineering teams.
• Own operational aspects of AI lifecycle: deployment, A/B testing, incident response, and continuous improvement.
• Contribute to AI strategy and roadmap, advising on operational feasibility and scalability of AI features.
• Collaborate with Principal Data Scientists and Principal Engineers to ensure MLOps framework supports full AI workflows and model interaction layers.

Machine Learning Operations Engineer, AI

Data Scientist

• Lead the design of AI systems that support complex, multi-step tasks, tool use, context adaptation, and intelligent decisions.
• Work closely with product and engineering to architect LLM-powered features that are robust, useful, and production-ready.
• Explore and implement RAG or Graph RAG approaches, including graph construction, entity linking, and hybrid scoring strategies.
• Design and implement LLM-powered systems for multi-step task automation, tool use, and context-aware reasoning.
• Contribute to prompt design and evaluate prompt results.
• Design and implement MLOps pipelines following best practices.
• Prototype, evaluate, and ship AI features using platforms like Claude or Amazon Bedrock with production readiness focus.
• Develop evaluation frameworks for model output quality, reliability, and alignment (e.g., hallucination detection, prompt regression, safety scoring).
• Embed AI capabilities into user workflows with engineers and designers to ensure meaningful product outcomes.
• Own the full lifecycle of AI components from evaluation and planning to testing, deployment, and continuous improvement.
• Contribute to AI strategy and roadmap to scale LLM usage responsibly across the platform.
• Collaborate closely with Principal Engineer to align AI workflows, system prompts, and model interaction layers.

Principal Data Scientist, AI

Business Development Rep

• As an Business Development Representative (BDR) at Opus 2, you will play a pivotal role in driving the growth of our business by identifying and engaging potential clients. You will generate leads, nurture relationships, and collaborate with the sales team to close deals.
• Research target accounts to identify key decision-makers to add into our CRM.
• Collaborate effectively within Sales and Marketing to optimize outreach strategies for better results.
• Personalize outreach messages to improve engagement and response rates.
• Work with sales to schedule meetings, demos, and presentations.
• Meet or exceed monthly and quarterly targets for lead generation and conversion.
• Identify and connect with potential clients via email, phone, and social media.
• Contact prospects aligned with marketing campaigns, events and targeted accounts.
• Assess the prospects’ needs, budget, and timeline to confirm a good fit.
• Contribute to testing new sales tools, scripts, and cadences for continuous improvement.
• Maintain accurate, up-to-date records of contacts , interactions, and deal progress in our CRM.
• Explore and understand legal trends, competitors, and market conditions.