Software Engineer (AI/ML/CV)

Brivo; Bengaluru; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

Brivo in Bangalore seeks a machine learning engineer to take end-to-end ownership of transforming complex problem statements into scalable, state-of-the-art ML solutions. You will operate at the intersection of data engineering, research, and deployment to build, optimize, and version high-impact models alongside a collaborative team of ML engineers.

You will work with LLMs, VLMs, and Transformer architectures to develop robust models and contribute across the ML lifecycle, including data

Qualifications

• Bachelors or Masters Degree in Computer Science or related disciplines.
• 2 - 4 years of experience required.
• At least 1 year of experience with LLMs/VLMs including architectures, training, datasets, and SOTA models.
• Strong theoretical and prior experience of CNNs and Transformers including usage in at least one product deployment.
• Fluency in Python Programming.
• Working knowledge of C/C++ desirable.
• Familiarity with ML Frameworks like PyTorch, TensorFlow etc.
• Familiarity with MLOps, including Model Quantization, annotation tools and model versioning tools like MLFlow.
• Strong background in Mathematics and Statistics.
• Sharp problem solving skills and ability to resolve ambiguous requirements.
• Familiarity with Dockers.

Responsibilities

• Handle all aspects of data filtering and agglomeration.
• Collaborate with other ML Engineers to brainstorm on best practices and updates on SOTA models.
• Translate problem requirements to architecture, codebase, and datasets; enhance in-house/open-source repos.
• Work with labeling teams to handle annotation metadata for datasets.
• Handle all aspects of the ML cycle including data preprocessing, augmentations, training, model/versioning, ablation studies and benchmarking.

Skills

Python programming

LLMs and VLMs

CNNs & Transformers

ML frameworks

MLOps

Docker

Mathematics & Statistics

Problem solving

C/C++ knowledge

Education

Bachelor's or Master's in Computer Science or related field

Tools

PyTorch

TensorFlow

MLFlow

Job description

Summary

In this role, you will take end-to-end ownership of converting complex problem statements into scalable, state-of-the-art machine learning solutions. Working at the intersection of data engineering, research, and deployment, you will harness LLMs, VLMs, and Transformer architectures to build, optimize, and version high-impact models alongside a collaborative team of ML engineers.

Location

Bangalore

Description

In this role, you will take end-to-end ownership of converting complex problem statements into scalable, state-of-the-art machine learning solutions. Working at the intersection of data engineering, research, and deployment, you will harness LLMs, VLMs, and Transformer architectures to build, optimize, and version high-impact models alongside a collaborative team of ML engineers.

Responsibilities

• Handle all aspects of data filtering and agglomeration.
• Collaborate with other ML Engineers to brainstorm on best practices, updates on SOTA models.
• Handle all translation of problem requirements to choice of architecture, codebase, and datasets. Enhancements of in-house/available open-source repositories to meet problem requirements.
• Work with data labeling teams to handle annotation metadata for your datasets.
• Handle all aspects of the Machine Learning cycle including data preprocessing, augmentations, training, model and experiment versioning, ablation studies and benchmarking.

Qualifications

• Bachelors or Masters Degree in Computer Science or related disciplines.
• 2 - 4 years of experience required.
• At least 1 year of experience with LLMs/VLMs including their architecture, training, datasets, and knowledge of SOTA models and frameworks to leverage these models.
• Strong theoretical and prior experience of CNNs and Transformers including their usage in at least one successful product deployment
• Fluency in Python Programming.
• Working knowledge of C/C++ desirable.
• Familiarity with ML Frameworks like Pytorch, TensorFlow etc.
• Familiarity with MLOps, including Model Quantization, usage of annotation tools and model versioning tools like MLFlow.
• Strong background in Mathematics and Statistics.
• Sharp problem solving skills and ability to resolve ambiguous requirements
• Familiarity with Dockers.

About Brivo

Brivo and Eagle Eye Networks have come together to create a category-defining, cloud-first platform at the intersection of AI and the physical world. Our mission is simple and ambitious: to make physical spaces safer, smarter, and more autonomous—from single-site businesses to global enterprises.

As the unified global leaders in cloud-based access control and video surveillance, we provide a comprehensive digital foundation for the built environment. By combining Brivo’s pioneering building access platform with Eagle Eye’s AI-powered video management system (VMS), we have created a system of intelligence that protects over 600 million square feet across 90+ countries. Every door, camera, and credential in our ecosystem acts as a real-time sensor, leveraging AI to prevent incidents, improve operations, and enable entirely new workflows across sectors, including commercial real estate, retail, healthcare, education, and critical infrastructure.

With a global footprint spanning headquarters in Bethesda, Maryland, and Austin, Texas, and international offices in Amsterdam, London, Bangalore, and Tokyo, we are leveraging our open APIs and cyber-secure cloud infrastructure to reshape the future of physical security. Join us as we build the world’s most robust platform for video intelligence and smart space automation. Learn more at www.brivo.com.

Brivo is an equal employment opportunity employer and values diversity. Qualified candidates are considered for employment without regard to race, religion, gender, gender identity, sexual orientation, national origin, age, military or veteran status, disability, or any other characteristic protected by applicable law. If you require reasonable accommodations during the application or interview process, please inform us.