Top Machine Learning Jobs in Hyderabad

Supports AI and analytics discovery by analyzing operational data and process flows, identifying inefficiencies, assessing AI/ML use cases, and generating business insights. Responsibilities include data exploration, analytical modeling, process mining, dashboard and visualization development, data-readiness assessment, documentation of assumptions and limitations, and collaboration with data scientists, business analysts, consultants, and architects. Healthcare domain experience is required.

Lead analytics function: define data strategy, ensure data quality, perform advanced statistical and ML analysis, build dashboards (Tableau/Superset/Power BI), provide actionable insights to stakeholders, collaborate across growth/risk/CRM/product, and drive continuous improvement in analytics practices.

Develops full-stack AI and machine learning applications using web technologies, statistical modeling, deep learning, databases, cloud platforms, and APIs. Designs algorithms, translates technical specifications into code, performs testing and debugging, documents solutions, and improves product and system performance. Works independently on complex initiatives, collaborates with stakeholders, mentors colleagues, and may manage projects or review others’ work.

Own core backend computation services that transform financial and operational data into correct, reproducible, traceable results. Design configuration-driven component libraries and runtimes, set-based warehouse computations, tenant-level guardrails, feature controls, audit logging, and data lineage. Build isolated, multi-cloud-ready customer-hosted deployments and integrate them with enterprise environments. Work directly with customer engineering and finance teams, establish backend architecture patterns, review designs, mentor engineers, and collaborate with data, AI, and product teams.

Early-career technologist supporting design, development, testing, deployment, and maintenance of applications, data pipelines, automations, and service management solutions. Assist requirements gathering, troubleshooting, QA, data tasks, and user support while following standards and learning new tools under senior guidance.

Leads the design, development, and delivery of scalable Python applications and cloud-native services. Defines architecture and technical standards, ensures code quality and application reliability, and resolves complex technical issues. Mentors developers, manages technical delivery, collaborates with cross-functional stakeholders, and supports Agile/Scrum planning and releases. The role also promotes responsible AI-assisted development and may work with data engineering technologies, messaging systems, observability tools, and machine learning frameworks.

Design, clean, analyze, and visualize data using SQL and Python; build Tableau dashboards; apply statistics and basic ML/DS concepts; follow software/data-engineering practices (version control, unit testing, high-performance code); work with structured and unstructured data and cloud environments.

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.

Work on AI/ML/Deep Learning models for new use cases, gain exposure to real-world industry data, produce written artifacts (articles), participate in guided knowledge-transfer sessions, and potentially earn recommendation or a pre-placement offer based on performance.

Develop, train, evaluate, and deploy small task-specific ML models for real-time English conversational skills (ASR, pronunciation, grammar, recommendations). Create datasets and task-specific evaluations, improve internal SOTA, mentor engineers, and contribute to hiring.

Develop and maintain high-performance 3D modeling software using advanced geometry processing, rendering, simulation, and visualization techniques. Integrate 3D assets, graphics APIs, game engines, and emerging VR, AR, and AI technologies. Build testing frameworks, troubleshoot complex issues, document software, conduct code reviews, provide technical support, and mentor junior developers while collaborating with designers, artists, engineers, and QA teams.

Develop and test C++ software for high-performance embedded Linux systems and automotive infotainment head units. Responsibilities include optimizing applications for x86, ARM, NEON, and CUDA architectures; designing software frameworks, modules, requirements, and interfaces; managing integration, builds, and releases; documenting designs and tests; and flashing and testing applications on embedded hardware. The role also involves supplier coordination, requirements clarification, and collaboration within Agile teams.

Develop end-to-end data science and AI/ML solutions involving statistical modeling, machine learning, generative AI, LLMs, NLP, and unstructured data analytics. Build data models and algorithms, solve ambiguous business problems, collaborate with project managers and multiple teams, and deliver actionable insights using cloud platforms such as AWS, Azure, or GCP. Present findings and communicate effectively with technical and business stakeholders.

Lead analytics and AI consulting engagements for CPG and retail clients. Structure complex business problems, design solutions, develop proofs of concept, advise executive stakeholders, manage client relationships, and deliver analytics transformation programs. The role also includes creating data assets, driving market adoption, recruiting and developing talent, and building analytics or AI communities of practice.

Develop and test C++ software for embedded Linux automotive infotainment head units. Responsibilities include optimizing applications for x86, ARM, NEON, and CUDA architectures; designing software frameworks and interfaces; analyzing requirements; managing integration, builds, and releases; documenting designs and tests; and developing, flashing, and testing applications on embedded hardware while collaborating with internal teams, suppliers, and partners.

The role requires a skilled Machine Learning Engineer to create complex models and AI solutions while collaborating with teams to enhance products and services.

Design, prototype, and deliver agentic AI solutions using ML and generative models. Partner with product, engineering, and delivery teams to build, evaluate, and deploy LLM-based solutions, run experiments and POCs, and communicate technical recommendations to stakeholders.

The Customer Success Business Partner at Lyric drives customer adoption and retention for strategic accounts, leveraging expertise in AI and supply chain operations.

Own end-to-end enterprise sales across Southeast Asia: prospecting, partner-led growth, channel management, demos, negotiation, forecasting, and closing. Build territory and partner plans, hit revenue quotas, represent CloudSEK to CISOs, collaborate with engineering, marketing and customer success, and manage onboarding and contract negotiations.

We are seeking a Director/VP of Sales for the USA market to develop sales strategies, lead a team, drive revenue, and build customer relationships in the cybersecurity sector.

Design, validate, and productionize ML/DL models for credit risk, propensity, fraud, and collections. Optimize algorithms for scalability, build monitoring frameworks, analyze large distributed datasets with Spark/PySpark, and contribute to agentic automation of the data science pipeline.

Lead product vision and discovery for a genomics-driven diagnostic and personalization platform. Validate hypotheses with patients, clinicians, and partners; translate research into product specs; coordinate labs and data providers; partner with engineers and researchers to build AI prototypes; shape data, regulatory, and GTM strategy while making core product and architectural decisions.

Build core components of a diagnostic and personalization platform: backend data pipelines, frontends, services for genomic data ingestion, ML model integration, APIs, and cloud infrastructure. Collaborate with product and ML teams, iterate on prototypes and MVPs, and make architectural decisions supporting scalability and reliability.

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.

Analyze e-commerce customer behavior and funnels to drive revenue growth, optimize pricing and retention, reduce costs across fulfillment and CAC, build dashboards and models, run A/B tests, and present insights to CXOs to improve profitability and marketing efficiency.