Graduate Systems Engineer in India

Software Engineer Build technology where every nanosecond matters. At Graviton, software isn't just a tool that supports trading. It is the infrastructure behind every research breakthrough, every trading decision and every competitive advantage. As a Software Engineer , you'll work on systems where performance, reliability and precision matter at an extraordinary scale. You'll partner closely with software engineers and quantitative researchers to build technology that processes enormous volumes of market data, powers quantitative research and supports live trading. You'll take on problems that don't have obvious answers — from designing high-performance systems and distributed infrastructure to eliminating bottlenecks measured in microseconds and building tools that make our researchers and engineers faster. Your work will go into production, be measured against real-world performance and have a direct impact on how our trading systems operate. If you enjoy solving hard engineering problems, understanding systems at a deep level and pushing technology to its limits, you'll feel right at home. What You'll Work On You'll work across the engineering stack that powers our quantitative research and trading platforms. Depending on your team, your work may include: Designing and building high-performance, low-latency systems in modern C++. Building distributed systems that process and analyze massive volumes of market data . Designing systems where latency, throughput and reliability directly influence trading performance . Working on Linux systems, networking, concurrency and multithreaded applications. Profiling systems, identifying bottlenecks and optimizing performance at the hardware and software level. Building robust infrastructure that supports quantitative research and live trading. Debugging complex production systems and solving problems where correctness and reliability are critical. Designing internal platforms and developer tools that accelerate research an

Education: Degree, Post graduate in Computer Science or related field (or equivalent industry experience) Experience: Minimum 5 years of Product experience in Finacle Core Banking product (Infosys/Edgeverve) Working experience on Finacle 11 requirement and product capability along with Customization architecture Experience in handling Finacle Interfacing requirements (Custom and Product APIs/Connect 24/Finacle Integrator) Need to have experience of direct interaction with Clients Technical Skills: Good understanding of Finacle Product Architecture & Customization layers. Finacle customization flow understanding (New custom menu, Reports - MRT & Jasper, Batch job, Product menu customization, FI, EOD-BOD process and debugging) Experience in best practices to be followed in Oracle (SQL, PL/SQL, Stored Procedures, Triggers, Functions) related to Finacle application. Experience in Finacle scripting, Unix shell scripting and Report designing. Good understanding of Finacle Integrator and feasible enhancements to the same. Functional Skills: Finacle Core Banking Functional knowledge Good understanding of Banking domain and terminologies used. Finacle certification from Infosys will be added advantage Finacle CRM and Admin module (FINFADM/SSOADM) Experience in following best Coding, Security, Unit testing and Documentation standards and practices Experience in Agile methodology. Ensure quality of technical and application architecture and design of systems across the organization. Effectively research and benchmark technology against other best in class technologies. Soft Skills: Able to influence multiple teams on technical considerations, increasing their productivity and effectiveness by sharing deep knowledge and experience. Self-motivator and self-starter, Ability to own and drive things without supervision and works collaboratively with the teams across the organization. Have excellent soft skills and interpersonal skills to interact and present the ideas

mthree Gradate Recruitment Program: Tech Roles About Us: mthree gives you a foot in the door to your dream career! We’ve helped 4,000 people start careers in technology, banking and business. For graduates and anyone starting their career, you’ll start with 6-12 weeks of training at our Academy. Then you’ll join one of our clients for 12-24 months (we work with investment banks and other big companies in industries from healthcare to aviation to insurance). You’re supported by us throughout, with pay rises every 12 months and an online learning plan to develop your skills. Afterwards, the majority continue their career with the client. At mthree, we believe in fairness from the start. We don’t lock you in with exit fees. You’ll never have to pay a thing. Join mthree to unlock your potential and go further than you thought possible. What you’ll do: If successful, you’ll work with one of our clients as an mthree Alumni designing, building, testing, and maintaining scalable and stable off-the-shelf applications or custom-built technology solutions. Also, working with a global team, you’ll help support systems including algorithmic trading engines and regulatory reporting. What you need: Degree in Computer Science, Technology, or related STEM subjects Academic aggregate of 60% or higher with no standing arrear Strong programming skills: Java/ Python/ C/ C++/ Others Competitive coding experience will be an added advantage Good troubleshooting and debugging skills Solid software engineering principles (data structures, OOPs, design patterns, multithreading) Understanding of the formal software development lifecycle (SDLC) Understanding of test-driven development How it works: Stage 1: Apply for the position Stage 2: Clear the first round of Aptitude & Coding assessment Stage 3: Clear communication Screening Stage 4: Clear Technical interview Stage 5: Clear Final interview Stage 6: Get selected to join the train

mthree Gradate Recruitment Program: Tech Roles About Us: mthree gives you a foot in the door to your dream career! We’ve helped 4,000 people start careers in technology, banking and business. For graduates and anyone starting their career, you’ll start with 6-12 weeks of training at our Academy. Then you’ll join one of our clients for 12-24 months (we work with investment banks and other big companies in industries from healthcare to aviation to insurance). You’re supported by us throughout, with pay rises every 12 months and an online learning plan to develop your skills. Afterwards, the majority continue their career with the client. At mthree, we believe in fairness from the start. We don’t lock you in with exit fees. You’ll never have to pay a thing. Join mthree to unlock your potential and go further than you thought possible. What you’ll do: If successful, you’ll work with one of our clients as an mthree Alumni designing, building, testing, and maintaining scalable and stable off-the-shelf applications or custom-built technology solutions. Also, working with a global team, you’ll help support systems including algorithmic trading engines and regulatory reporting. What you need: Degree in Computer Science, Technology, or related STEM subjects Academic aggregate of 60% or higher with no standing arrear Strong programming skills: Java/ Python/ C/ C++/ Others Competitive coding experience will be an added advantage Good troubleshooting and debugging skills Solid software engineering principles (data structures, OOPs, design patterns, multithreading) Understanding of the formal software development lifecycle (SDLC) Understanding of test-driven development How it works: Stage 1: Apply for the position Stage 2: Clear the first round of Aptitude & Coding assessment Stage 3: Clear communication Screening Stage 4: Clear Technical interview Stage 5: Clear Final interview Stage 6: Get selected to join the train

mthree Gradate Recruitment Program: Tech Roles About Us: mthree gives you a foot in the door to your dream career! We’ve helped 4,000 people start careers in technology, banking and business. For graduates and anyone starting their career, you’ll start with 6-12 weeks of training at our Academy. Then you’ll join one of our clients for 12-24 months (we work with investment banks and other big companies in industries from healthcare to aviation to insurance). You’re supported by us throughout, with pay rises every 12 months and an online learning plan to develop your skills. Afterwards, the majority continue their career with the client. At mthree, we believe in fairness from the start. We don’t lock you in with exit fees. You’ll never have to pay a thing. Join mthree to unlock your potential and go further than you thought possible. What you’ll do: If successful, you’ll work with one of our clients as an mthree Alumni designing, building, testing, and maintaining scalable and stable off-the-shelf applications or custom-built technology solutions. Also, working with a global team, you’ll help support systems including algorithmic trading engines and regulatory reporting. What you need: Degree in Computer Science, Technology, or related STEM subjects Academic aggregate of 60% or higher with no standing arrear Strong programming skills: Java/ Python/ C/ C++/ Others Competitive coding experience will be an added advantage Good troubleshooting and debugging skills Solid software engineering principles (data structures, OOPs, design patterns, multithreading) Understanding of the formal software development lifecycle (SDLC) Understanding of test-driven development How it works: Stage 1: Apply for the position Stage 2: Clear the first round of Aptitude & Coding assessment Stage 3: Clear communication Screening Stage 4: Clear Technical interview Stage 5: Clear Final interview Stage 6: Get selected to join the train

Job Description (JD) for MEP Engineer - Electrical Lead Projects & Site Integration. Experience Minimum 8 to 12 years of relevant experience in industrial pharmaceutical FMCG chemical manufacturing or process industry projects. Proven experience in handling electrical systems control systems for greenfield and brownfield projects. Experience in project execution commissioning and plant integration activities. Technical Competencies Electrical power distribution systems (HT/LT) Transformers switchgear MCCs PCCs UPS and DG systems Load calculations and power system studies Earthing and lightning protection systems Electrical safety standards and statutory compliance FAT SAT commissioning and start-up support Technical Bid Analysis (TBA) Vendor and contractor management AutoCAD and electrical drawing review Project planning and execution methodologies Excellent stakeholder management and communication skills Problem-solving and troubleshooting mindset Result-oriented with strong project ownership Effective planning organizing and execution skills Address: D-3/CL, MIDC Industrial Area,Turbhe, Navi Mumbai. 400705 Facility: ZOETIS PHARMACEUTICAL - NAVI MUMBAI Qualification: Post graduate Experience: 8 - 12 years Source: Sodexo India | Job Code: IJP575825

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Who you are You are an experienced Infrastructure Engineer Engineer who owns backend infrastructure end to end. You design multi-tenant, microservices-based systems that other engineering teams build on, and you make deliberate architectural tradeoffs around consistency, latency, scale, and cost. You are comfortable going deep — service mesh internals, database internals, distributed-systems failure modes — and equally comfortable defining the reliability and security contracts an enterprise AI platform depends on. Responsibilities Design, own, and evolve scalable microservices architectures on Kubernetes across GCP, Azure, and AWS, including multi-tenant isolation (namespaces, network policies, per-tenant resource quotas and RBAC). Build core platform and data-plane components in Golang and Python — data ingestion, knowledge-base indexing and vector/graph search, application connectivity, workflow automation, and ML operations — against explicit latency and throughput SLOs. Own service-to-service communication: gRPC/protobuf API contracts, service mesh (Istio/Linkerd), load balancing, retries, timeouts, and circuit breaking. Make and document architectural tradeoffs — partitioning

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Who you are You are an experienced Platform Engineer who owns backend infrastructure end to end. You design multi-tenant, microservices-based systems that other engineering teams build on, and you make deliberate architectural tradeoffs around consistency, latency, scale, and cost. You are comfortable going deep — service mesh internals, database internals, distributed-systems failure modes — and equally comfortable defining the reliability and security contracts an enterprise AI platform depends on. Responsibilities Design, own, and evolve scalable microservices architectures on Kubernetes across GCP, Azure, and AWS, including multi-tenant isolation (namespaces, network policies, per-tenant resource quotas and RBAC). Build core platform and data-plane components in Golang and Python — data ingestion, knowledge-base indexing and vector/graph search, application connectivity, workflow automation, and ML operations — against explicit latency and throughput SLOs. Own service-to-service communication: gRPC/protobuf API contracts, service mesh (Istio/Linkerd), load balancing, retries, timeouts, and circuit breaking. Make and document architectural tradeoffs — partitioning/sharding strat

Data Engineer Description - Key Roles Designs and establishes secure and performant data architectures, enhancements, updates, and programming changes for portions and subsystems of data pipelines, repositories or models for structured/unstructured data. Analyzes design and determines coding, programming, and integration activities required based on general objectives and knowledge of overall architecture of product or solution. Writes and executes complete testing plans, protocols, and documentation for assigned portion of data system or component; identifies and debugs, and creates solutions for issues with code and integration into data system architecture. Collaborates within a project team of other data engineers to develop reliable, cost effective and high-quality solutions for assigned data system, model, or component. Analyzes data inaccuracies, identifies opportunities and supports the development of automated solutions to enhance overall quality of the enterprise data. Identifies problematic areas and conducts research to determine the best course of action to correct the data; identifies, analyzes and interprets trends and patterns in complex datasets. Works cross-functionally with different departments to assess, define, and develop report deliverables. Represents the software data engineering team for all phases of larger and more-complex development projects. Provides guidance and mentoring to less experienced staff members. Education & Experience Recommended Four-year or Graduate Degree in Computer Science, Information Technology, Software Engineering, Statistics/ Mathematics, or any other related di

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Role Overview & Key Responsibilities This is a high-leverage leadership role that spans architecture, execution, and org-building, and will shape the direction of our AI / ML initiatives at Ema. We are seeking an AI / ML technical leader who can take a vision and build it. As a Principal ML Engineer at Ema, you will be a senior technical leader responsible for shaping the machine learning roadmap, architecting large-scale ML systems, driving innovation, and ensuring our mixture of expert models (LLM + SLM + Custom Model) is accurate and performant at scale. You will collaborate across teams (research, product, infra, data, etc.), mentor senior engineers, and influence strategy and execution at company-wide levels. Responsibilities Lead the technical direction of GenAI and agentic ML systems that power enterprise-grade AI agents — spanning reasoning, retrieval, tool use, and integrations across various SaaS products. Architect, design, and implement scalable production pipelines for model training, fine-tuning, retrieval (RAG), agent orchestration, and evaluation — ensuring robustness, latency efficiency, and continuous learning. Define and own the multi-year ML roadmap for GenA

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. About the Role As a Site Reliability Engineer at Ema, you will own the stability, availability, and operational health of our agentic AI platform across customer environments. You'll work closely with Engineering and DevOps to provision infrastructure, drive deployment excellence, and keep production running at the quality bar our enterprise customers expect — 99.9%+ uptime, proactive incident response, and continuous improvement. What You'll Do Infrastructure & Deployment Design and provision cloud infrastructure (GCP, Azure, AWS) tailored to customer environments, with security, scalability, and compliance built in Execute on-call SaaS deployments with minimal downtime; automate and optimize deployment workflows end-to-end Production Stability & Observability Monitor logs, alerts, and metrics to maintain SLA commitments and catch issues before they escalate Diagnose and resolve production incidents with speed and rigor; drive root cause analysis and permanent fixes Collaborate with DevOps to enhance monitoring dashboards and alerting frameworks; deliver clear system health reporting to internal and customer stakeholders Documentation & Knowledge Management Maintain de

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. About the role As Ema scales, our corporate IT environment tools, access, devices, and compliance has outgrown an ownership-by-default model. We're hiring an IT Engineer to own it end to end. This is not a traditional helpdesk role. Ema is an agentic AI company, and we expect our own internal operations to reflect that. You'll run corporate IT while systematically automating it, using agentic tooling to remove the manual work rather than absorbing it. The measure of success in this role is how little of it remains manual after a year and every employee’s experience is great. What you'll do Agentic Workflows & Automation: Treat every recurring manual task as an automation candidate, extending existing systems and leveraging AI coding tools to design autonomous workflows. Automated Identity & Access: Shift JML lifecycles, including global employee onboarding, Okta/SCIM provisioning, and access reviews from ticket-driven processes to policy-driven automation. SaaS Lifecycle Automation: Programmatically maintain tool inventories, track utilization, and reclaim unused licenses automatically. Automated Endpoint Security: Manage fleet MDM while automating OS patching, encryption b

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Who you are We're looking for an innovative and passionate Machine Learning Engineers to join our team. You are someone who loves solving complex problems, enjoys the challenges of working with huge data sets, and has a knack for turning theoretical concepts into practical, scalable solutions. You are a strong team player but also thrive in autonomous environments where your ideas can make a significant impact. You love utilizing machine learning techniques to push the boundaries of what is possible within the realm of Natural Language Processing, Information Retrieval and related Machine Learning technologies. Most importantly, you are excited to be part of a mission-oriented high-growth startup that can create a lasting impact. You will: Conceptualize, develop, and deploy machine learning models that underpin our NLP, retrieval, ranking, reasoning, dialog and code-generation systems. Implement advanced machine learning algorithms, such as Transformer-based models, reinforcement learning, ensemble learning, and agent-based systems to continually improve the performance of our AI systems. Lead the processing and analysis of large, complex datasets (structured, semi-structured, and

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Who we are Ema is building the next generation AI technology to empower every employee in the enterprise to be their most creative and productive. Our proprietary tech allows enterprises to delegate most repetitive tasks to Ema, the AI employee. We are founded by ex-Google, Coinbase, Okta executives and serial entrepreneurs. We’ve raised capital from notable investors such as Accel Partners, Naspers, Section32 and a host of prominent Silicon Valley Angels including Sheryl Sandberg (Facebook/Google), Divesh Makan (Iconiq Capital), Jerry Yang (Yahoo), Dustin Moskovitz (Facebook/Asana), David Baszucki (Roblox CEO) and Gokul Rajaram (Doordash, Square, Google). Our team is a powerhouse of talent, comprising engineers from leading tech companies like Google, Microsoft Research, Facebook, Square/Block, and Coinbase. All our team members hail from top-tier educational institutions such as Stanford, MIT, UC Berkeley, CMU and Indian Institute of Technology. We’re well funded by the top investors and angels in the world. Ema is based in Silicon Valley and Bangalore, India. This will be a hybrid role where we expect employees to work from office three days a week. Who you are We are seeking an

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Who are you? We are seeking an experienced Enterprise Software Engineer to join the Ema team in India. As an Enterprise Software Engineer, you will be responsible for designing, developing, and maintaining our enterprise software applications. You will work with a cross-functional team of product managers, designers, and developers to deliver high-quality software solutions that meet the needs of our enterprise clients. The ideal candidate has experience building products across the stack and a firm understanding of web frameworks, APIs, databases, and multiple back-end languages. Most importantly, you are excited to be part of a mission-oriented, fast-paced, high-growth startup that can create a lasting impact. You will: Develop and maintain enterprise software applications, including API, data, application, and service development Write clean, efficient, and maintainable code by employing test-driven development process. Build scalable and reliable back-end systems using languages like Go and Python. Develop and maintain APIs using REST, gRPC or GraphQL Integrate multiple enterprise applications and services using a scalable framework like FastAPI Build and maintain data schema u