Machine Learning Engineer
Cognite - AI for Industry —Bengaluru, Karnataka
- Computer science
- Azure
- Computer Science
Quick apply
3h
Principal Search/AI Engineer
Grid Dynamics —India
- Full-time
- Hybrid work
- Azure
- DevOps
- Research
- Health insurance
- Flexible schedule

More jobs to discover

Find similar jobs that you might be interested in.

Principal Search/AI Engineer
Grid Dynamics —India
You will collaborate with our established search practice to design, build, and optimize AI-powered search platforms that deliver rich content and product…

I want to receive the latest job alerts for ml engineer signal processing /

By signing in to your account, you agree to SimplyHired's Terms of Service and consent to our Cookie and Privacy Policy.

Explore jobs in more locations

ml engineer signal processing / jobs near

Machine Learning Engineer jobs in Bengaluru, Karnataka

Machine Learning Engineer jobs in Visakhapatnam, Andhra Pradesh

Machine Learning Engineer jobs in Kanniyakumari, Tamil Nadu

Machine Learning Engineer jobs in Nagpur, Maharashtra

Machine Learning Engineer jobs in Dehradun, Uttarakhand

Printing Machine Operator jobs in Bawana, Delhi, Delhi

Sewing Machine Mechanic,garments,textile jobs in Ahmedabad, Gujarat

Computer Engineer jobs in Rajkot, Gujarat

Principal Software Engineer jobs in Remote

Principal jobs in Andhra Pradesh

Principal Software Engineer jobs in Tamil Nadu

Software Developer jobs in Vadodara, Gujarat

Software Engineer jobs in Allahabad, Uttar Pradesh

Principal Software Engineer jobs in Bhanpur, Bhopal, Madhya Pradesh

Principal Software Engineer jobs in Bengaluru, Karnataka

Machine Learning Engineer

Cognite - AI for Industry
Bengaluru, Karnataka

Quick apply

Job details

3 hours ago

Qualifications

TensorFlow
Computer science
Image processing
Azure
Computer Science
Software Engineering
PyTorch
Computer vision
Data structures
Master's degree
Databases
SQL
Pandas
AWS
Docker
Bachelor's degree
Machine learning
REST
Natural language processing
APIs
Linux
JSON
Apache
Data science
Flask
gRPC
Python
Data Science

Full job description

What Cognite is: Relentless to achieve

Cognite operates at the forefront of industrial digitalization, building AI, and data solutions that solve the world's hardest, highest-impact problems. With unmatched industrial heritage and a comprehensive suite of AI capabilities, including low-code AI agents, Cognite accelerates the digital transformation to drive operational improvements.

We thrive in challenges. We challenge assumptions. We execute with speed and ownership. If you view obstacles as signals to step forward - not backwards - you'll feel right at home here.

Our Moonshot is bold: Unlock $100B in customer value by 2035, and redefine how global industry works. Join us in this venture where AI and data meet ingenuity, and together, we will forge the path to a smarter, more connected industrial future.

About the Opportunity

We are building the next generation of contextual AI for Industrial Operations. Our team focuses on transforming unstructured, complex industrial data—ranging from technical manuals to complex piping and instrumentation diagrams (P&IDs)—into structured, actionable intelligence. We leverage state-of-the-art Deep Learning, Generative AI, and Computer Vision to drive efficiency, safety, and operational excellence.

About the Role

As a Machine Learning Engineer, you will be a key contributor to building the models and pipelines that power our industrial contextualization platform. Working closely with senior and staff-level engineers, you will focus on execution—transforming research prototypes into high-performance, real-time applications and building the infrastructure that supports them.

This is an engineering-first role. We seek hands-on builders who write production-grade code, understand system design, and tackle complex infrastructure, treating ML models as software components in a large industrial architecture—not pure data scientists building isolated models.

How you'll demonstrate Ownership

You love writing clean, readable code and seeing it work. You are deeply curious about how complex ML systems operate in the real world and are passionate about turning raw data into robust, reliable pipelines.
You don't just write research scripts; you want to build durable software. You know how to take a well-defined technical plan, execute it efficiently, and ask the right questions when you hit roadblocks. You prioritize building things the right way the first time over quick, fragile hacks.
You are eager to absorb new paradigms in MLOps, containerization, and model deployment, applying feedback rapidly to improve your craft.

The Impact you bring to Cognite

Key Responsibilities

Build, test, and maintain robust data pipelines for large-scale industrial datasets.
Assist in deploying data science prototypes to production.
Write high-quality, testable Python code, primarily creating RESTful/gRPC APIs for ML capabilities.
Containerize applications (Docker) and navigate Linux to handle massive volumes of unstructured industrial data.
Run experiments, fine-tune existing foundational models (NLP, Vision-Language), and evaluate ML libraries to enhance document parsing and entity matching.
Write rigorous unit/integration tests and monitor deployed models for drift and performance.
Collaborate closely with senior staff (engineers, data scientists, product managers) to deliver features on the technical roadmap.

Required Skills and Qualifications

Bachelor's or Master's degree in Computer Science, Data Science, Software Engineering, or a related field.
3–6 years of industry experience in software engineering with a strong focus on machine learning, or vice versa.
Strong programming skills in Python, with a proven ability to write clean, modular, and testable code.
Solid hands-on experience with frameworks like PyTorch, TensorFlow, Hugging Face, or LangChain.
Experience working with large datasets, writing complex SQL queries, and hands-on familiarity with data processing libraries or frameworks (e.g., PySpark, Pandas at scale, or Dask)
Familiarity with MLOps basics, containerization (Docker), Linux command-line tools, and fundamental cloud services (AWS, Azure, or GCP).
Solid understanding of core computer science fundamentals, data structures, and algorithms.

What Sets you Role Apart

The ability to take a well-defined technical problem or architecture plan from a principal engineer and write highly efficient, bug-free code to solve it.
A rapid trajectory in absorbing new paradigms (like vector databases or agentic workflows) and efficiently applying them to massive volumes of real-world industrial data without crashing the system.
A commitment to treating ML code like production software, never skipping the tests or the documentation.

Preferred Qualifications / Good to Haves

Academic or early industry experience with Vision-Language Models (VLMs) or Computer Vision (e.g., document layout analysis).
Hands-on familiarity with basic RAG pipelines and Vector Databases (e.g., Pinecone, Milvus, Qdrant). Exposure to agentic frameworks (e.g., LangGraph).
Exposure to modern columnar data (e.g., Parquet) or data lakes (e.g., Delta Lake, Apache Iceberg). Understand efficient querying/chunking of large unstructured data for ML.
Experience with highly unstructured data, including text and JSON extraction from messy PDFs using OCR. OT dataset exposure is a plus.
Experience serving models via backend web frameworks (FastAPI/Flask). Comfortable troubleshooting Linux permissions, fonts, and dependencies.

Learn more about us

Impact 2025
Cognite's Industrial AI: Moonshot
We're globally recognized domain experts with an international presence that spans Phoenix, Houston, Oslo Tokyo, Bengaluru, and Abu Dhabi.

Equal Opportunity

Cognite is committed to creating a diverse and inclusive environment at work and is proud to be an equal opportunity employer. All qualified applicants will receive the same level of consideration for employment.

Quick apply

Refine Your Search

ml engineer signal processing / jobs