Company Description Nexthink is the leader in digital employee experience management software. The company provides IT leaders with unprecedented insight allowing them to see, diagnose and fix issues at scale impacting employees anywhere, with any application or network, before employees notice the issue. As the first solution to allow IT to progress from reactive problem solving to proactive optimization, Nexthink enables its more than 1,300 customers to provide better digital experiences to more than 18 million employees. Dual headquartered in Lausanne, Switzerland and Boston, Massachusetts, Nexthink has 9 offices worldwide. #LI-Hybrid Job Description Are you passionate about AI and eager to drive innovation in a fast-paced, impact-driven environment? Do you have experience developing AI-powered applications and enjoy mentoring others? If so, we invite you to join Nexthink as a Senior ML Engineer! As a key member of our AI team, you will design, develop, and deploy scalable AI solutions, leveraging cutting-edge technologies to enhance digital employee experiences for millions worldwide. Responsibilities - Lead AI Development - Design and implement AI-powered products, with a strong focus on Agentic systems. - LLMs done right - Create evaluations and define metrics of success using cutting edge AI platforms. - MLOps - Implement and manage MLOps practices to streamline the deployment, monitoring, and maintenance of models and in production environments. - Collaboration & Leadership - Work closely with software engineers, data scientists, and product teams to align AI capabilities with business needs. - Mentorship & Coaching - Guide and support junior AI engineers, fostering a culture of learning and knowledge sharing. Qualifications - Bsc/Master's degree in Computer Science, Machine Learning, Data Science, or a related field. - 5+ years of hands-on experience in LLM-powered production applications. - Strong proficiency in Python and AI frameworks (e.g., LangChain, PyTorch). - Proven experience with AWS and cloud-based AI deployments. - Solid understanding of AI model fine-tuning, optimization, and evaluation. - Excellent problem-solving skills and ability to work in a fast-paced, collaborative environment. - Eagerness to learn and adapt - Strong communication skills in English, capable of explaining complex AI concepts to technical and non-technical stakeholders - we believe in learning by sharing - Knowledge of reinforcement learning, retrieval-augmented generation (RAG), and multi-agent AI architectures. - Strong data intuition: ability to inspect raw logs, design metrics and quickly identify quality regressions - Hands-on experience with MLOps: reproducible pipelines, automated evaluations, feature stores, CI/CD for models or prompt/embedding configs - Familiarity with MLOps best practices for deploying and monitoring AI models in production. If you're excited about pushing the boundaries of AI and mentoring the next generation of engineers, we'd love to hear from you! Even if you don't meet every requirement, we encourage you to apply-we value expertise, passion, and the drive to learn. Additional Information We are the pioneers and trailblazers of a global IT Market Category (DEX) that is shaping the future of how the world works, giving our customers' IT Teams total digital visibility across their enterprise. Our innovative solutions integrate real-time analytics, automation, and employee feedback across all endpoints. This enables our IT teams to solve complex technical challenges, create ever more productive workplaces, and deliver happy, satisfied employees in the digital workplace. With over 1000 employees across 5 continents, Nexthink operates as One Team, connecting, collaborating and innovating to continuously grow. We call our employees 'Nexthinkers' and our commitment to diversity, inclusion, and equity is second to none. We currently have over 75 nationalities working with us, from all cultures and backgrounds, speaking many different languages. If you are looking for a change and like a nice atmosphere, lots of challenges, and having fun while working, this is a great opportunity for you! Check what we offer: - Permanent Contract and a competitive compensation package. - Beautiful office with a view of Lake Geneva, conveniently located next to the Prilly-Malley train station - Hybrid work model balancing office and remote work, with a structured approach for new hires to foster connections and onboarding. - Flexible Hours and unlimited vacation (employees have unlimited paid time off on top of the 25 days of holidays we offer) plus 3 company-paid volunteer days. - Free access to a fitness centre inside the building. - Reimbursement of the half-fare travel card for public transport. - ‍ Reimbursement up to 50% of the cost of French classes. - Fresh fruit, cookies, and soft drinks as well. - Regular company and team events like Voluntary Days, Pizza talks, Team Building activities, hosting Meetups at the office and more! - Bonuses for referring successful hires after three months of continuous employment. - We offer a relocation package to people who are coming from another country. Please note that not all the benefits listed above are available for temporary, contract, and internship roles. To ensure you have the most up-to-date information, we recommend checking with your Recruitment Partner.

Role Description We are hiring a Founding AI/ML Engineer to architect and ship production-grade AI systems transforming one of the world’s largest and least automated industries — construction. This is a product-first AI engineering role focused on multimodal intelligence, document understanding, and agentic workflow automation. You will work directly with the Chief AI Officer and founders to move from low-automation to high-automation mode, where AI agents perform core operational work with light human oversight. Qualifications - 6+ years of engineering experience - Experience at an early-stage, high-growth startup - Shipped production-grade AI systems to real customers - Hands-on LLM and/or computer vision experience - Retrieval systems experience (embeddings, chunking, grounding) - Agentic workflow experience (tools, APIs, state management, retries, guardrails) - Strong backend fundamentals: - APIs - Async jobs / queues - Databases - Cloud deployment - Monitoring - Full end-to-end ownership mindset Requirements - Build and ship production-grade AI systems used daily by real customers - Design multimodal pipelines for drawings, specs, and construction documents - Build agentic workflows automating preconstruction tasks: - Document intake - Extraction - Takeoff support - Bid preparation - QA workflows - Build and improve: - Retrieval systems (embeddings, reranking, chunking) - Evaluation systems - Orchestration layers - Optimize model quality, latency, reliability, and cost efficiency - Prototype and iterate quickly on customer-facing AI features - Own systems end-to-end (experiment → deploy → monitor → improve) - Help shape engineering culture and long-term technical direction Benefits - Meaningful early-employee ESOP grant - Employer-funded health insurance (Patch model) - Team / meal stipend - Growth path to technical leadership (optional management track)

Role Description The Hartford is seeking a Staff AI Machine Learning Engineer to build Machine Learning Operations (MLOps) services for the Middle and Large Business Applied AI team. You will play a critical role in designing, building, and operationalizing production-grade AI and ML solutions, partnering closely with product, engineering, and platform leaders to deliver measurable impact. - Research, experiment with, and implement suitable Generative AI and ML algorithms, tools, and technologies. - Participate in identifying and assessing opportunities, i.e., value of new data sources and analytical techniques and technology, to ensure ongoing competitive advantage. - Review work with leadership and partners on an ongoing basis to calibrate deliverables against expectations. - Accountable for deployment design, development, and maintenance of both traditional ML and AI models. - Work with junior engineers and peers to provide mentorship and thought leadership. Be comfortable presenting new concepts to technical audiences. - Collaborate with partners in Enterprise Data, Applied AI, Business, Cloud Enablement Team, and Enterprise Architecture teams. - Delivery of critical milestones for model deployment in the AWS and GCP clouds. - Adopt and promote MLOps best practices to the Data Science community. Qualifications - Bachelor’s degree in related field or 7+ years of equivalent experience in a Research, Engineering, Data Science, or DevOps Role. - Development experience developing solutions within AWS, GCP, or both. - Experience developing repeatable architectural patterns; ability to identify redundancies and eliminate them with these patterns. - Experience building and deploying API services within the Cloud. - Experience building CICD pipelines. - Experience with IAC (Infrastructure as Code) including Cloud Formation, Terraform, or equivalents. - Experience in Unix, git, and strong object-oriented development experience using Python. - Experience in end-to-end model development lifecycle, from ideation through post-production monitoring. - Experience with workflow automation platforms (Apache Airflow, Autosys, similar). - Basic understanding of Data Science model development life cycle. - Familiarity with emerging data-centric technologies such as generative AI, Agentic workflows, and embedding LLMs into automated processes. Requirements - Must be authorized to work in the U.S. now and in the future. - Candidate must be authorized to work in the US without company sponsorship. The company will not support the STEM OPT I-983 Training Plan endorsement for this position. Benefits - The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency, and demonstration of competencies required for the role. - The annualized base pay range for this role is: $125,760 - $188,640. - Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition.

• Develop and maintain machine learning models that are integral to our production decision-making system and directly influencing business outcomes. • Adopt or build new technologies for training and serving ML models (e.g. support large models, increase developer velocity, etc) • Monitor the latest ML research for functional ideas that the team could try. • Optimize ML Pipelines – Build and scale efficient pipelines for real-time and batch processing. • Model Monitoring & Improvement – Track performance, detect drift, and automate retraining. • Use strong communication skills (verbal and written) to explain statistical and machine learning concepts to both technical and non-technical audiences • Collaborate with a team of world-class engineers with diverse backgrounds. • Be part of an “engineering excellence” culture through state-of-the-art tools, risk-driven testing, explainable systems, and code review.