Top Machine Learning Jobs in Bengaluru

Designs, develops, and deploys software solutions for digital pathology and medical imaging systems. Integrates imaging algorithms and machine vision models with industrial cameras, robotics, automation tools, and production systems. The role requires strong C++ and Python skills, system design expertise, parallel processing, multithreading, and CUDA-based GPU programming. Experience with OpenCV, machine learning, and imaging pipelines is preferred.

Develop and optimize Deep Packet Inspection solutions for 4G/5G systems. Responsibilities include creating traffic signatures, analyzing application flows and network packets, working with Wireshark and PCAP files, building traffic simulation and automation tools, troubleshooting traffic issues, and researching DPI engine improvements. The role requires strong C programming, operating systems and networking knowledge, with Python, reverse engineering, and ML-based traffic classification as advantages.

Develop and enhance ServiceNow CMDB, ITOM, and ITSM solutions with AI-driven automation, AIOps, GenAI, intelligent incident routing, and predictive insights. Build workflows, integrations, applications, and automation using JavaScript, Glide scripting, REST APIs, Flow Designer, Business Rules, and Script Includes. Configure Discovery and Event Management, translate business requirements into scalable solutions, collaborate with stakeholders, and optimize existing ServiceNow applications while following security, governance, performance, and scalability standards.

Build and maintain mission-critical wealth management systems for SMB clients. Design data pipelines, ETL/ELT processes, data models, warehouses, analytics, and reporting solutions using AWS, Snowflake, Mage AI, and other big data tools. Collaborate with data scientists and analysts on predictive models, statistical analyses, and machine learning algorithms. Develop software with Next.js and Python while working closely with the team and clients on financial-domain challenges.

Leads a multidisciplinary engineering team building Testsigma’s AI agent platform, knowledge graph infrastructure, and core product. Owns engineering delivery, software quality, platform reliability, SLOs, incident response, hiring, team development, product partnership, and customer-facing technical escalations. Collaborates with product and go-to-market teams to prioritize roadmap commitments, address reliability concerns, and ensure high-quality releases.

Design and build scalable backend microservices, distributed systems, event-driven architectures, data pipelines, and real-time analytics for procurement, logistics, credit, and compliance. Lead cloud infrastructure, CI/CD, observability, security, performance tuning, and reliability initiatives across high-throughput systems. Apply machine learning and automation to vendor recommendations, demand forecasting, risk scoring, and fraud detection while driving engineering standards through code reviews and cross-functional collaboration.

Lead the architecture and implementation of high-volume distributed payment systems spanning settlement, ledgers, treasury, fraud, AML, and stablecoin infrastructure. Establish engineering standards, solve scalability and reliability challenges, promote AI-assisted development, evaluate AI-driven product opportunities, collaborate across business and engineering teams, and mentor senior technical leaders.

The role involves developing software tools for semiconductor compilers, creating an ecosystem for efficient IP generation, and requires knowledge in circuit design and programming.

Develop and implement software for robotic systems focusing on navigation, planning, and integration of machine learning models.

As a Senior Backend Engineer, you will design and maintain scalable software solutions, embrace innovation with AI tools, and ensure high-quality engineering practices.

Design, build, and maintain backend APIs and services for a real-time supply chain visibility platform. Own system architecture, real-time event ingestion, data normalization, ML integration, monitoring, and production debugging while collaborating with Product and Data Science to deliver scalable, high-availability features.

Build, test, and deploy scalable backend components (primarily Django/Python). Implement algorithms and subsystems for lending and user communications. Solve complex engineering problems with simple designs. Collaborate cross-functionally and perform analytics using SQL to inform product and marketing decisions.

The Principal Software Engineer will define architectural strategy, solve complex technical challenges, mentor teams, and guide future platform development at Loop AI.

The Data Engineer will develop and maintain data-crawling infrastructure, work with teams to gather requirements, write efficient code, and mentor juniors.

Lead backend architecture and engineering: design scalable APIs and services, mentor engineers, write complex code, enforce best practices for databases, testing, observability, and integrate ML/LLM workloads.

Lead development and optimization of astrodynamics algorithms for orbit determination, propagation, conjunction analysis, and prediction. Design, validate, and operationalize scalable, efficient SSA software; research ML/AI and numerical methods; mentor junior engineers; collaborate across software, data science, operations, and product teams; contribute to documentation, proposals, and publications.

The Application Engineer will collaborate with customers in the automotive, aerospace, and energy industries to solve engineering challenges through machine and deep learning, utilizing Python to process data and develop tailored workflows, while providing training and translating customer feedback into product improvements.

As a Technical Account Manager, you will drive customer adoption of AI-driven simulation tools, engage with engineering teams, and support software implementation in design workflows.

As a Demo Engineer, you support pre-sales by designing AI-driven demos and proof of concepts, collaborating closely with teams to showcase Cresta's capabilities.

Design and implement ML infrastructure for scalable deployment, collaborate across teams, optimize ML systems, and enhance tooling.

Develop and optimize machine learning models, manage project priorities, and improve real-world solutions using advanced ML techniques.

As a Senior Machine Learning Engineer, you'll build LLM-powered agents, collaborate on experiments, support prompt engineering, and monitor AI features in production.