Machine Learning Engineer (GenAI) at Spector.ai

Mountain View, California, United States -

Full Time

Start Date

Immediate

Expiry Date

07 Aug, 26

Salary

0.0

Posted On

09 May, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Generative AI, Agentic Workflows, Knowledge Graphs, Multimodal Extraction, Distributed Infrastructure, Machine Learning Training, ML Inference, ML Evaluation, Cloud Environments, Scalable ML Architectures, Statistical Modeling, Edge LLM Deployment, Industrial Asset Management, Cross-functional Collaboration, Technical Leadership, System Design

Industry

Software Development

Description

Role Description We are seeking an experienced GenAI engineer to join our seasoned founding team to drive the development and innovation of our GenAI platform. Ideal candidates bring experience in building agentic workflows, knowledge graphs, and multimodal extraction systems for enterprise use cases. This role requires a hands-on engineer who is passionate about our mission, thrives in a startup environment, and is committed to pushing the boundaries of what AI can achieve in industrial resilience. You will: Lead engineering initiatives aimed at the continuous enhancement of the AI platform, with a focus on the rapid development and iteration of scalable, robust distributed infrastructure to support machine learning training, inference, and evaluation. Hands-on contributor and overseer of GenAI workflow development and deployment across multiple clusters and cloud environments. Define and articulate the long-term strategic vision for Spector’s GenAI platform. Mentor and guide junior engineers, fostering a culture of growth, collaboration, and innovation within the technical team. Must Have: Bachelor's Degree in a relevant technical field such as computer science and 3+ years of post-Bachelor’s ML + GenAI experience; or Master’s degree in a technical field and 2+ year of post-grad ML + GenAI experience; or PhD in a relevant technical field and 1 years of post-grad ML + GenAI experience. Understanding of the unique challenges and constraints in deploying AI solutions. Have a track record in deploying scaled ML systems. Demonstrated experience designing and implementing scalable GenAI/ML architectures capable of handling high data volume and complex data structures. Strong communication skills with the ability to convey complex technical concepts to both technical and non-technical stakeholders. Experience in cross-functional team alignment and collaborating closely with domain experts, engineers, and product specialists. Entrepreneurial Mindset: Highly motivated and adaptable with a passion for innovation, problem-solving, and making a meaningful impact in a startup environment. Willingness to take ownership and drive projects from concept to implementation, Good to have: Past experience in ML and statistical modeling. Past experience in Industrial space or familiarity with industrial operations, asset management, or reliability. Building genAI system with real-time responsiveness and edge-llm deployment. Compensation Competitive compensation package that includes salary and equity. Comprehensive health benefits: Medical, Dental, and Vision. About Spector.ai Spector.ai is a well-funded seed-stage startup on a mission to solve the $1.5 trillion challenge of industrial asset reliability. Spector is building an AI-first industrial agent platform designed to transform plant reliability and performance optimization using an agentic first approach. By combining machine learning and domain-specific industrial AI Agents, Spector.ai enables real-time diagnostics, root cause analysis, and actionable recommendations at scale. The platform extracts insights from complex industrial data, including unstructured documentation and live sensor streams, reducing false positives, shortening time to resolution, and scaling expertise without reliance on data scientists. As an industry leader at the forefront of AI-driven plant performance and health, Spector.ai is experiencing rapid growth through new client acquisitions and key industrial alliances while actively generating revenue.

Responsibilities

Lead the development and strategic vision of a GenAI platform focused on industrial resilience and asset reliability. This includes building scalable distributed infrastructure and overseeing the deployment of agentic workflows across cloud environments.