Top Machine Learning Jobs in Kolkata

Build scalable, low-latency backend APIs, event-driven services, integration layers, and microservices supporting personalization and recommendation experiences. Partner with AI/ML and data engineers to deploy models, expose AI services, and develop React applications. Improve security, observability, reliability, performance, scalability, and operational efficiency while using AI-assisted engineering tools to enhance delivery and code quality.

Design, build, test, deploy, and maintain innovative distributed software systems. Lead technical direction and feature roadmap for a critical international expansion function, optimize service performance and security, and operate in an agile environment. The role includes significant autonomy, cross-functional communication, and opportunities to hire and shape the engineering team. Candidates should have strong computer science fundamentals, modern software development experience, and familiarity with cloud, databases, frontend frameworks, machine learning, and DevOps technologies.

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.

Lead technical direction and delivery for a core NIRA backend domain: design and ship high-volume web APIs, own architecture for distributed and queue-based systems, drive complex initiatives, mentor engineers, lead incident response, champion AI dev tools, and align cross-functionally to simplify systems and influence roadmap.

Design and develop scalable full-stack features using Java, Spring Boot, Python, FastAPI, Angular, and Azure. Lead technical decisions, backend architecture, API design, code reviews, engineering standards, deployment strategies, CI/CD improvements, cloud deployments, and observability. Collaborate with product, data science, and design teams to build AI-powered user experiences, contribute technical insights to roadmap planning, and balance hands-on coding with technical leadership.

Own and improve the Command|Alert alerting platform, including rule evaluation, anomaly detection, event correlation, reliable Kafka and OpenSearch pipelines, and downstream notifications. Convert security and network telemetry into usable topologies and dependency maps, support LLM-based alert generation, resolve production issues, lead reliability improvements, deliver independent projects, and mentor engineers while shaping technical direction.

Leads the creation and scaling of AmeriSave’s India technology organization, including recruiting, engineering culture, architecture, software platforms, cloud infrastructure, AI initiatives, security, budgets, and global collaboration. The CTO partners with U.S. executives, oversees distributed engineering teams, drives delivery and operational excellence, and aligns technology strategy with business goals. The role requires extensive executive leadership, India team-building experience, software engineering depth, cloud expertise, and experience with AI and emerging technologies.

Designs and develops content governance platforms, anti-abuse tools, rule engines, and scalable governance pipelines. Integrates recommendation systems, implements content takedown policies, and builds capabilities for content review, risk detection, policy enforcement, and effectiveness analysis. The role addresses spam, fraud, traffic diversion, low-quality content, and black- or gray-market activity while collaborating with product, operations, algorithm, and business teams.

Design, develop, and maintain high-performance, secure Java backend services and APIs. Ensure reliability, scalability, and cost-efficiency across microservices, databases, messaging systems, and capacity planning. Troubleshoot, profile, benchmark, and optimize systems (including ML applications) and collaborate with Kazakhstan stakeholders.

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.

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.

Early-career Performance Engineer in the Binance Accelerator Program. Perform hands-on performance testing and tuning, design AI-powered test strategies using LLMs and ML, build AI-driven anomaly detection and bottleneck analysis tools, research new AI technologies, and improve reliability of large-scale distributed systems.

The Staff Engineer in Machine Learning will guide teams, solve client challenges, and enhance solutions leveraging their technical expertise.

Lead an 8-10 engineer team owning courier systems (dispatch, matching, pricing, ETA). Set technical direction, drive data-driven decisions and experiments, partner with data science, ensure reliability and scalability of low-latency distributed systems, and own hiring, performance, and operational excellence.

Lead architecture and development of the core native iOS SDK and related apps. Own feature delivery from design to public release, write high-quality tested code, collaborate with R&D and ML teams, support customers to resolve issues, and manage priorities across large-scale, distributed projects.

The role involves developing enterprise applications using Java and Spring, integrating AI features, mentoring junior developers, and collaborating with cross-functional teams.

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 Python and Kubernetes Software Engineer, you will develop data analytics solutions using open source tools, collaborating with a distributed team.