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At Weights & Biases, our mission is to build the best tools for AI developers. We founded our company on the insight that while there were excellent tools for developers to build better code, there were no similarly great tools to help ML practitioners build better models. Starting with our first experiment tracking product, we have since expanded our solution into a comprehensive AI developer platform for organizations focused on building their own deep learning models and generative AI applications.
Weights & Biases is a Series C company with $250M in funding and over 200 employees. We proudly serve over 1,000 customers and more than 30 foundation model builders including customers such as OpenAI, NVIDIA, Microsoft, and Toyota.
We're hiring an AI Solutions Engineer, Post Sales to help our customers solve difficult, real-world problems and engage in ground-breaking research by using our developer tools in their machine learning pipelines.
In this role, you'll be working with the most sophisticated ML/GenAI teams in the world working on some of the toughest ML/GenAI problems in computer vision, robotics, natural language processing, Large Language Models (LLMs), and more. You'll have the opportunity to work with ML/GenAI teams across multiple industries to uncover their ML/GenAI needs, improve their ML/GenAI workflow, explore how Weights & Biases fits into their environment, collaborate on projects, and educate them on the best practices of our product.
Solutions Engineers on our Field Engineering team play a vital role in the success of our customers at Weights & Biases. You'll collaborate with the Sales, Support, Product, and Engineering teams to lead the technical success of our customers after the sales process, acting as the primary source of knowledge and representative to our customers. You will play a key role in customer adoption, partnering with our product team to steer product development based on customer feedback and usage patterns.
This is an ideal opportunity for anyone with machine learning experience who is customer-focused and eager to work with the top ML/AI companies globally, focusing on ensuring customer success and adoption post-sales.
Responsibilities:
- Master the implementation of complex ML pipelines and GenAI applications for engineering teams, leveraging Weights & Biases products, to ensure smooth customer onboarding and adoption processes.
- Serve as a trusted advisor to new customers by identifying their desired outcomes and clearly communicating Weights & Biases’ product best practices, ensuring their success through effective integration and optimization in the post-sales adoption phase.
- Serve as a pivotal link between customers and internal R&D teams by continuously providing customer feedback and advocating for customer needs, thereby directly influencing the product roadmap and enhancements to reflect real user experiences, trends, challenges, and successes.
Requirements:
- 3-5 years of relevant experience in a similar role
- Strong programming proficiency in Python and an eagerness to help ML and GenAI application builders through knowledge of deep learning frameworks like TensorFlow/Keras, PyTorch Lightning, and tools such as Streamlit, LangChain, etc.
- Excellent communication and presentation skills, both written and verbal
- Ability to effectively manage multiple conflicting priorities, respond promptly, and manage time effectively in a fast-paced, dynamic team environment
- Ability to break down complex problems and resolve them through customer consultation and execution.
- Experience with cloud platforms (AWS, GCP, Azure)
- Experience with Linux/Unix
Strong Plus:
- Experience with GenAI and LLMs
- Proficiency with one or more of the following packages: HuggingFace, Fastai, scikit-learn, XGBoost, LightGBM, Ray
- Experience with hyperparameter optimization solutions
- Experience with data engineering, MLOps, LLMOps, and tools such as Docker and Kubernetes
- Experience with data pipeline tools
Our Benefits:
- 🏝️ Flexible time off
- 🩺 Medical, Dental, and Vision for employees and Family Coverage
- 🏠 Remote first culture with in-office flexibility in San Francisco
- 💵 Home office budget with a new high-powered laptop
- 🥇 Truly competitive salary and equity
- 🚼 12 weeks of Parental leave (U.S. specific)
- 📈 401(k) (U.S. specific)
- Supplemental benefits may be available depending on your location
- Explore benefits by country
We encourage you to apply even if your experience doesn't perfectly align with the job description as we seek out diverse and creative perspectives. Team members who love to learn and collaborate in an inclusive environment will flourish with us. We are an equal opportunity employer and do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. If you need additional accommodations to feel comfortable during your interview process, reach out at careers@wandb.com.
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What you need to know about the Seattle Tech Scene
Home to tech titans like Microsoft and Amazon, Seattle punches far above its weight in innovation. But its surrounding mountains, sprinkled with world-famous hiking trails and climbing routes, make the city a destination for outdoorsy types as well. Established as a logging town before shifting to shipbuilding and logistics, the Emerald City is now known for its contributions to aerospace, software, biotech and cloud computing. And its status as a thriving tech ecosystem is attracting out-of-town companies looking to establish new tech and engineering hubs.
Key Facts About Seattle Tech
- Number of Tech Workers: 287,000; 13% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Amazon, Microsoft, Meta, Google
- Key Industries: Artificial intelligence, cloud computing, software, biotechnology, game development
- Funding Landscape: $3.1 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Madrona, Fuse, Tola, Maveron
- Research Centers and Universities: University of Washington, Seattle University, Seattle Pacific University, Allen Institute for Brain Science, Bill & Melinda Gates Foundation, Seattle Children’s Research Institute
