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About brighthush – Pioneering AI‑Powered Customer Experiences
At brighthush, we’re not just building software; we’re redefining how enterprises interact with their customers and marketplaces. Our mission is to fuse human expertise with cutting‑edge AI agents, creating solutions that are fast, cost‑effective, and contextually aware. From content moderation to fraud detection, from customer support to complex workflow automation, our technology empowers businesses to eliminate repetitive tasks while preserving the nuanced judgment that only humans can provide.
Founded by seasoned technologists and industry veterans, brighthush has secured significant venture capital backing. Though we operate at a substantial scale, we remain in an early‑growth phase, giving you the unique opportunity to shape our product roadmap, influence our culture, and leave a lasting imprint on the future of AI‑powered customer solutions.
Why brighthush is a Game Changer
Digital interactions are exploding at an exponential rate, and the need for intelligent, context‑aware automation has never been greater. brighthush sits at the forefront of this transformation, building AI agents that understand the subtleties of human language, visual content, and business workflows. Our ambition is simple yet bold: create an online world free from harm, where AI can make safe and fair decisions without complex technical integration.
We’re assembling a team of passionate, collaborative, and forward‑thinking individuals eager to push the boundaries of what’s possible. If you thrive in a fast‑paced, high‑impact environment and want to see your work transform real businesses, brighthush is the place for you.
Role Overview
As a Senior Full‑Stack Machine Learning Engineer, you will serve as the bridge between our customers’ operational challenges and the AI solutions we deliver. Your mission is to translate complex workflows into intelligent, autonomous agents that deliver measurable value. You’ll start by providing hands‑on support for our machine learning models as they go to market, then evolve into building self‑service tools that enable customers to achieve outcomes independently.
Your Impact & Day in the Life
Every day at brighthush is a blend of deep technical work, customer collaboration, and strategic thinking. A typical day might look like:
- Morning Sync: Quick stand‑up with the product and customer success teams to review the latest customer feedback and prioritize feature requests.
- Model Development: Design, train, and fine‑tune deep learning models using state‑of‑the‑art neural network libraries, ensuring they meet the highest standards of accuracy and efficiency.
- Customer Workshops: Conduct workshops with clients to map out their workflows, identify pain points, and translate business requirements into technical specifications.
- Platform Enhancement: Contribute to the evolution of our Virtual Agent development platform, adding features that support rapid deployment and easy customization for customers.
- Code Review & Mentorship: Review pull requests from junior engineers, provide constructive feedback, and share best practices for MLOps and AI ethics.
- Performance Monitoring: Set up and maintain observability pipelines, ensuring that every agent operates reliably at scale.
- Evening Reflection: Document insights, update knowledge bases, and plan for the next day’s experiments.
Key Responsibilities
- Customer Collaboration: Work closely with clients to map out their workflows, pain points, and success metrics. Translate these insights into technical requirements for AI automation.
- Virtual Agent Design: Architect and build AI agents that automate end‑to‑end processes, ensuring they are reliable, observable, and performant at scale.
- Platform Development: Contribute to the evolution of our Virtual Agent development platform, adding features that support rapid deployment and easy customization for customers.
- Quality Assurance: Implement rigorous testing, monitoring, and observability pipelines to guarantee high standards of reliability and performance.
- Community Leadership: Participate in brighthush’s internal ML community, shaping best practices for computer vision, natural language processing, and agentic AI.
- Full‑Stack Ownership: Own the end‑to‑end lifecycle of AI solutions—from data ingestion and model training to deployment, monitoring, and continuous improvement.
- Customer Success: Own customer outcomes, making data‑driven decisions that surprise and delight clients while aligning with brighthush’s mission.
- Project Management: Manage timelines, deliverables, and cross‑functional dependencies to ensure timely delivery of high‑quality AI products.
- Innovation Advocacy: Champion new research, tools, and frameworks that can accelerate our product roadmap and improve customer value.
- Ethics & Governance: Embed responsible AI principles into every stage of model development and deployment.
Essential Qualifications
- 5+ years of experience in machine learning engineering, with a strong focus on applied AI solutions.
- Proficiency in Python and deep learning libraries, with a track record of building and deploying production‑ready models.
- Hands‑on experience building and deploying AI agents that automate human processes.
- Solid understanding of container orchestration and cloud infrastructure.
- Excellent communication skills—able to translate technical concepts to non‑technical stakeholders.
- Product mindset: a genuine curiosity for solving customer challenges and a passion for delivering tangible value.
- Comfortable working in a collaborative, cross‑functional environment where teamwork outweighs individual accolades.
- Willingness to travel to company‑wide off‑sites three times per year.
- Strong analytical and problem‑solving skills, with a track record of delivering production‑ready AI solutions.
Preferred Qualifications
- Experience in a fully remote, international team setting.
- Prior startup experience, especially in AI or SaaS.
- Background in building and operating agentic AI systems.
- Proficiency with MLOps tools and production monitoring.
- Knowledge of CI/CD pipelines and deployment automation.
- Strong SQL and NoSQL database skills.
- Experience with Infrastructure as Code tools.
- Familiarity with large language models and a keen interest in staying current with AI advancements.
- Experience with data privacy regulations (GDPR, CCPA) and data‑centric security practices.
Skills & Competencies
- Deep learning model design and optimization.
- Data pipeline engineering and feature engineering.
- Model deployment, scaling, and monitoring in production.
- Containerization and orchestration with container platforms.
- Version control and collaborative development practices.
- Problem‑solving and analytical thinking.
- Strong written and verbal communication.
- Adaptability and resilience in a fast‑moving startup environment.
- Leadership and mentorship abilities.
Tools & Tech Stack
At brighthush, we leverage a modern, cloud‑native stack that empowers rapid experimentation and reliable production. Your day‑to‑day toolkit will include:
- Programming: Python and deep learning libraries.
- Data & Storage: Relational and NoSQL databases, object storage.
- Orchestration: Container orchestration platform.
- MLOps: Model registry, training pipelines, and deployment automation.
- CI/CD: Git‑based version control and automated pipelines.
- Observability: Monitoring stack, log aggregation, and visualization dashboards.
- Infrastructure: Infrastructure as Code tools.
- Collaboration: Communication, knowledge base, and design tools.
Success Metrics
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