We are looking for an AI Developer Advocate to join our Developer Relations team. In this role, you will help promote MongoDB's artificial intelligence (AI) capabilities. As more developers choose MongoDB as their data platform, your responsibilities will include directly engaging with the community, building strategic partnerships with AI companies, creating inspiring resources and content, and collaborating with a global team of skilled Developer Advocates.

You will empower developers—from startups to Fortune 500 companies—to integrate advanced data and AI capabilities into their applications and solutions. If you are passionate about helping builders explore the possibilities of AI and enjoy cultivating a vibrant developer ecosystem, we invite you to join us in shaping the future of development on MongoDB.

Our Developer Relations teams are distributed across the globe, with most members working remotely. This position will be based in the San Francisco Bay Area. To see what our team is doing, check out our content on YouTube, Dev, and Medium.

We are looking to speak to candidates who are based in San Francisco for our hybrid working model.

Candidate Profile

We are excited to welcome an influential individual to our team who is already a well-established voice in AI. From your experience over the past few years, we’ll see you in videos and at events sharing technical insights, leading discussions, and inspiring others to effectively use AI and ML capabilities. You’ve also created articles, tutorials, and hands-on workshops to teach builders best practices and equip them to leverage AI in their apps. 

At the foundation of your passion and expertise is a love to equip others. Our ideal candidate will have at least 3 years of experience in a builder role, such as a data scientist or developer, where they crafted AI solutions in production. They will have 8+ total years of experience through any combination of builder role (such as data scientist or developer), educator role (such as developer advocate or developer educator), or customer-facing role (such as solution architect). 

Our ideal candidate will also have connections with AI companies and communities in the San Francisco Bay Area. You will work with key AI partners to create content and partner on virtual and in-person events that showcase how MongoDB is part of the larger AI ecosystem. 

You are an effective teacher who can explain complex topics in a simple and easy-to-understand way. Along with an appreciation for the key AI-related features of our platform, such as vector search and Voyage AI, you will also develop a strong understanding of MongoDB's core capabilities, data modeling, and emerging trends in our industry.

Though the expertise you bring will be unique, our team is built to work together to share knowledge and help each other grow. You will work with others at all levels, supporting peer reviews of code, demos, sessions, and other content. You should have a genuine passion for equipping other developers to be more productive and successful. 

Position Expectations

Below are examples of the types of work you will be doing. Your mix of activities will vary week to week based on priorities and event schedules. 

• Build on a solid foundation of ML/AI expertise, adding to your database experience to become a MongoDB expert
• Expand your knowledge of embedding models and rerankers to become an expert in Voyage AI
• Collaborate with our events and field teams to engage developers and founders in the Bay Area at meetups, events, hackathons, and startup houses
• Speak at strategic AI events and lead workshops at high-profile conferences such as AWS re:Invent 
• Create and update tutorials, articles, videos, and workshops along with their associated workflows or workflows or code examples
• Provide feedback to our Product and Technology team, serving as the voice of the developer as new products are scoped and planned
• Regularly interface with Partner Managers to identify opportunities to work with key AI partners to create content and partner on virtual and in-person events that showcase how MongoDB is part of the larger AI ecosystem 
• Partner with our community team to support engagement with third-party and first-party user groups (MUGs), Champions, and influencer programs across the region
• Lead one-hour sessions (both virtual and in-person) with customer teams to evaluate their AI use cases and provide recommendations on how they can better utilize MongoDB

Requirements

• Expertise in building AI or ML solutions and comfortable building agentic solutions
• Advanced familiarity with several AI coding and workflow tools, and how platforms are recommended through content, preference, and integration
• Expertise with one or more complementary programming languages (Python or JavaScript preferred)
• Knowledgeable and connected in the Bay Area AI ecosystem
• Prolific author of content (tutorials, how-to guides, readmes) and associated code to help developers learn
• Established portfolio or active contributor to AI examples and Agent Skills in GitHub
• Engaging presenter at in-person events, videos, webinars, or live streams 
• Up to 25% of time traveling to Bay Area engagements (like meetups, events, hackathons, and startup houses)
• Up to 10% of time traveling outside of the Bay Area for industry events 

About MongoDB

MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform—the most widely available, globally distributed database on the market—helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and nearly 60,000 customers—including 75% of the Fortune 100 and AI-native startups—relying on MongoDB for their most important applications, we’re powering the next era of software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. 

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.

MongoDB, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type and makes all hiring decisions without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Req ID: 1273376493

Mission Summary:

At Motional, we're transforming how autonomous vehicles discover critical intelligence hidden within petabytes of multimodal sensor data. Our next-generation autonomous driving stack depends on finding the rare edge cases, long-tail scenarios, and model errors that matter most. Omnitag, our ML-powered multimodal data mining framework, is the engine that powers this discovery.

As a Senior Machine Learning Engineer on the Data Mining team, your mission is to build the "Brain" of this engine: designing massive multimodal Teacher models that understand the world, and distilling them into hyper-efficient Student models that can scour exabytes of data in near real-time. You will work at the intersection of large-scale representation learning, retrieval optimization, and reasoning systems. Your work will directly influence how we compress knowledge into efficient encoders for fast search, and how we apply reinforcement learning to optimize data discovery workflows and intelligent querying. By building smarter mining tools, you will accelerate the entire model improvement lifecycle for teams working on post-training analysis, error diagnosis, and dataset curation.

What You'll Do:

• Architect and Train Distilled Models: Design and implement teacher-student model frameworks for multimodal sensor data. Develop training pipelines for knowledge distillation. Ensure student models maintain high accuracy while drastically reducing inference latency and memory footprint.
• Reinforcement Learning for Data Discover: Build RL-based policy learning and reasoning systems for autonomous driving applications. Implement and scale RL training workflows (e.g., PPO, DQN, actor-critic methods) for simulation and real-world interaction. Explore reward shaping, environment modeling, and multi-agent RL where applicable.
• Optimize Model Deployment for Real-Time Inference: Collaborate with backend engineers to deploy distilled and RL models into production. Optimize for latency, throughput, and hardware efficiency across GPU/CPU clusters. Implement model versioning, A/B testing, and monitoring for performance regressions.
• Research and Integrate Agentic Systems: Explore and prototype agentic workflows for autonomous reasoning, chain-of-thought prompting, and goal-directed behavior. Integrate such systems into our broader autonomy stack as experimental or production components.
• Drive Production Reliability: Establish patterns for graceful degradation, fault tolerance, and cost optimization. Operate Omnitag as a mission-critical data platform serving the entire ML organization, with a focus on reliability, debuggability, and operational excellence.
• Mentor and Collaborate: Work closely with ML scientists, data engineers, and autonomy teams to translate research advances into scalable engineering solutions. Guide junior engineers in best practices for model training, evaluation, and deployment.

What We're Looking For:

• BS in Computer Science, Machine Learning, or related field, or equivalent professional experience.
• 6+ years of hands-on experience in machine learning engineering, with a focus on model post training, optimization, and deployment.
• Strong experience with model distillation or teacher-student training - practical knowledge of loss functions, training strategies, and evaluation of compressed models.
• Proven experience with reinforcement learning in production or research settings: policy optimization, reward design, simulation environments, and RL-based reasoning.
• Expert-level proficiency in Python and ML frameworks (PyTorch, TensorFlow, or JAX).
• Strong software engineering fundamentals: testing, CI/CD, containerization, and system design.
• Experience deploying ML models in cloud environments (AWS, GCP, or Azure) and optimizing for inference.
• Demonstrated ability to ship production-grade ML systems and mentor team members.
• Demonstrated track record of shipping robust, well-tested, production-grade systems and mentoring junior engineers

Bonus Points (Nice-to-Haves):

• MS/PhD in Computer Science, Machine Learning, or related field.
• Experience with agentic systems, autonomous reasoning, chain-of-thought models, or LLM-based planning.
• Background in autonomous driving, robotics, or real-time decision-making systems.
• Familiarity with multimodal learning, sensor fusion, or embodied AI.
• Experience building active learning loops, using the model to find the data that breaks the model.
• Experience with ML-based data mining, active learning, or contrastive learning.
• Knowledge of model serving tools (TF Serving, Triton, TorchServe) and MLOps platforms.
• Publications or open-source contributions in RL, distillation, or efficient ML.
  
  

We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote.

Whether you have experience as a teacher, outside sales representative, or management, insurance, finance, or business ownership experience, you can be successful here. As an Exclusive Agent, you have excellent earning potential, access to a professional training program, and the opportunity to help provide solutions specifically geared to and priced for educators.

The Insurance Agent works directly with the Regional Field Leader (Agency Consultant).

You Will Enjoy

• A performance-based compensation package.
• Competitive performance-based compensation.
• Earning incentives based upon activity in the initial 48 months.
• Earning quarterly production incentives for the first 48 months.
• No External Office Requirement.
• A dedicated Premier Service Rep to assist with client service work.
• A niche market to increase your opportunity for success.
• Technology and continued training to support your base of operations.
• A multi-line product portfolio; and
• Market and relationship-building programs

You Possess the Following

• Strong interpersonal and business management skills while building your agency.
• 2-4 years of experience in the insurance and financial services industry preferred; and
• Gain appropriate insurance licenses (Required - Life & Health, Property & Casualty)
• Gain FINRA Series 6 & 63 if applicable in certain regions.

Responsibilities

• Be dedicated to solving the financial challenges educators face.
• Excel at gaining market access and building relationships.
• Be comfortable presenting information to potential customers one-on-one and in large groups.
• Attend networking, community, sales, and industry events; and
• Be willing to invest time and resources to ensure business success.

Horace Mann Educators Corporation

We're the country's most comprehensive multiline insurance and financial services company serving educators. At Horace Mann, we know educators take care of our children's future, and we believe they deserve someone to look after theirs.

We're an equal opportunity employer

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