Machine Learning Engineer
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Before you apply
LocationBengaluru
Work modehybrid
Typefull-time
SeniorityMid
Experience1+ yrs
DepartmentEngineering
Company size7+ people
PostedDec 13, 2025 · 10mo ago
Verified live1d ago
At a glanceSummarised by Seekless from the posting.
Bachelor's Degree in a relevant technical field such as computer science and 3+ years of post-Bachelor’s machine learning experience
Master’s degree in a technical field + 2+ year of post-grad machine learning experience
PhD in a relevant technical field + 1 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
Experience working with machine learning frameworks such as TensorFlow, PyTorch, Spark ML, scikit-learn, or related frameworks
Ability to work with both internal and external partners
Strong collaboration and mentorship skills
Entrepreneurial Mindset: Highly self 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
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
Skills
TensorFlow
PyTorch
Spark ML
scikit-learn
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 engineer 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:
•
Create ML models which help drive value for users and our company.
•
Build scalable ML model training and serving infrastructure.
•
Evaluate the technical tradeoffs of every decision.
•
Perform code reviews and ensure exceptional code quality.
•
Iterate quickly without compromising quality.
Must Have:
•
Bachelor’s Degree in a relevant technical field such as computer science and 3+ years of post-Bachelor’s machine learning experience; or Master’s degree in a technical field + 2+ year of post-grad machine learning experience; or PhD in a relevant technical field + 1 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.
•
Experience working with machine learning frameworks such as TensorFlow, PyTorch, Spark ML, scikit-learn, or related frameworks.
•
Ability to work with both internal and external partners.
•
Strong collaboration and mentorship skills.
•
Entrepreneurial Mindset: Highly self 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.aiis 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.