Role Description
We are seeking an experienced machine learning engineer to join our seasoned founding team to drive the development and innovation of our ML platform. Ideal candidates bring extensive experience in building the next generation of machine learning models and its training and serving infrastructure for the Spector.
This role requires a hands-on tech lead who is passionate about our mission, thrives in a startup environment, and is committed to pushing the boundaries of what ML and GenAI can achieve in industrial resilience.
You will:
- Lead engineering initiatives aimed at the continuous enhancement of the ML platform, build high quality models to model drive value for users and our company.
- Hands-on contributor and overseer of ML workflow to build scalable, robust distributed infrastructure to support machine learning training, inference, and evaluation.
- Evaluate the technical tradeoffs of every decision.
- Perform code reviews and ensure exceptional code quality.
- Mentor and guide junior engineers, fostering a culture of growth, collaboration, and innovation within the technical team.
- Iterate quickly without compromising quality.
Must Have:
- Bachelor's Degree in a relevant technical field such as computer science and 6+ years of post-Bachelor’s machine learning experience; or Master’s degree in a technical field + 5+ year of post-grad machine learning experience; or PhD in a relevant technical field + 3 years of post-grad machine learning experience.
- Experience developing machine learning models for supervised, unsupervised, ranking, or other relevant applications of machine learning.
- Strong understanding of machine learning approaches and algorithms.
- Have a track record in deploying scaled ML systems.
- Experience working with machine learning frameworks such as TensorFlow, PyTorch, Spark ML, scikit-learn, or related frameworks.
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,
Preferred to have:
- Experience in on-prem ML model deployment and observability.
- Experience in building and deploying ML models for real time time series data like sensor/IoT data.
**About Spector.ai
Spector.ai**is a well-funded, fast-paced, innovative seed-stage startup focused 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 from reactive to autonomous operations. 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.
We are rapidly growing and looking for an experienced, self-driven DevOps Engineer to join our core team. This is a unique opportunity to shape our infrastructure, tooling, and deployment practices from the ground up, ensuring we can scale effectively and reliably as we move toward our next stage of funding and growth.