• Field service Engineer supporting all da Vinci® Surgical platforms • Analyze customer’s requirements to ensure effective system installation • Ability to autonomously manage and schedule both planned and unplanned appointments • Assess and determine follow up visits to ensure maximum system reliability • Use discretion and independent judgment when assessing the functionality of Intuitive Surgical products • Provide training for customer staff in troubleshooting and system management best practices • Develop rapport with hospital staff including surgeons, robotics coordinators, and MEs • Monitor metrics and customer feedback to ensure that work style aligns to the customer’s needs

• be the primary pre- and post-sales technical support contact for MPS key customers in the South Central, US Area • engage with key customers and secure design wins using MPS power products and services • define and share current and emerging customer power technical needs to improve the tactical and strategic product positioning • work closely with local sales team and product lines • contribute to MPS US Revenue growth through direct and in-direct technical activities • identify and win new business opportunities • develop solid technical understanding of power products and relevant solutions • share technical knowledge to build trust and confidence with customer power engineering team • provide frequent on-site technical support to customers • provide regular feedback to product lines and help define new products • gather potential market changes and competitors’ activities for MPS product strategy • act as local subject matter expert presenting MPS power products and technology to key customers.

• Provide remote support in France for the customer Mistral, with a combination of dedicated support and helpdesk support

Role Description AI Field Engineers at Fireworks are the technical tip of the spear. You embed with our most ambitious customers and technology partners to turn complex AI problems into production systems, fast. The role sits at the intersection of engineering, product, and customer delivery. You are hands-on-keyboard building POCs, MVPs, and production integrations, while also holding your own in executive-level conversations about architecture, strategy, and business outcomes. - You spend most of your time building. - You ship code, run benchmarks, debug production issues, and architect deployments. - You lead discovery conversations, align stakeholders, and translate customer pain points into product improvements. - This is a role for engineers who are comfortable on-site with customers, building relationships and trust in person. Qualifications - 5+ years in a hands-on, customer-facing technical role: Forward Deployed Engineer, Applied AI Engineer, Solutions Architect, ML Engineer with field exposure, or technical founder. - Demonstrated ability to build production software with customers, not just advise on it. - Strong Python skills. Comfortable reading, writing, and debugging production code. - Familiarity with Kubernetes and infrastructure engineering. - Working knowledge of the LLM stack: inference trade-offs, model serving, fine-tuning workflows (SFT at minimum; DPO/RFT a strong plus). - Experience with cloud infrastructure (AWS, Azure, GCP) and deploying models on GPU infrastructure. - Exceptional communication skills. - Experience building or integrating agentic systems, tool-use chains, or AI-native developer toolchains. Requirements - Build end-to-end POCs and MVPs alongside customer engineering teams. - Architect the inference foundations that capability depends on for customers whose core product is built on GenAI. - Run load tests and establish latency, throughput, and cost baselines against realistic customer traffic profiles. - Deploy and validate new model families on inference frameworks (vLLM, SGLang). - Guide customers on model selection, fine-tuning strategy (SFT, DPO, RFT), and evaluation methodology. - Build and run fine-tuning pipelines directly with customers. - Design and implement evaluation frameworks that measure production-quality metrics. - Help customers bake frontier model capabilities into their core offering. - Lead structured discovery conversations to unpack customer pain points, constraints, and success criteria. - Own the technical relationship from first engagement through production deployment. - Spend time on-site with customers to build trust and momentum. - Identify recurring customer pain points and translate them into concrete product proposals. - Codify repeatable deployment patterns and contribute them back to internal tooling. - Feed customer signals back into the product roadmap with specificity and urgency. Benefits - Total compensation includes meaningful equity in a fast-growing startup. - Competitive salary and comprehensive benefits package. - Base salary is determined by individual qualifications, experience, skills, interview performance, market data, and work location. - On Target Earnings (Plus Equity): $200,000 — $260,000 USD.