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System Engineer (ECU)

Location: Hyderabad

Fulltime

Your tasks as Specialist System Engineer ECU(m/f):

• Analysis of the requirements for the electronics control of occupant safety systems in alignment to the customer specifications
• Definition of the System Requirements for the embedded system
• Ensuring quality requirements according to ASPICE and ASIL (ISO 26262)
• Definition of the design and architecture of the ECU system taking into account the latest technologies and continuous improvement ideas using SYSML
• Coordination and functional leadership of the project team from hardware and software development

Your profile as Specialist Systems Engineer ECU(m/f):

• Successfully completed engineering studies in electronics, embedded system, or software
• Several years of professional experience in the development of control units within the automotive industry
• Experience in product development according to ASPICE and ISO 26262
• Assertiveness, target-oriented and structured working methods, ability to work in a team
• Willingness of intercultural work environment.

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Byteridge is seeking a Rapid Prototyping Engineer specializing in AI Infrastructure & Optimization to work with our most strategic customers on deploying, fine-tuning, and optimizing large language models at scale. You will be at the forefront of Byteridge's AI infrastructure capabilities, helping customers unlock the full potential of foundation models through expert-level deployment on GPU infrastructure.

This highly technical role requires deep expertise in machine learning infrastructure, GPU optimization, and production ML systems, combined with the ability to translate complex technical concepts into customer success.

What You'll Do

Model Deployment & Optimization

• Lead end-to-end deployments of large language models on AWS infrastructure for strategic

customers

• Design and implement training, fine-tuning, and inference pipelines using Amazon SageMaker AI

• Optimize model performance through GPU-level tuning, kernel optimization, and infrastructure

configuration

• Deploy models on diverse GPU architectures including NVIDIA and AWS custom silicon (Trainium,

Inferentia)

Infrastructure Architecture & Performance

• Architect scalable ML infrastructure using SageMaker AI Inference, HyperPod, and distributed

training frameworks

• Implement CUDA-level optimizations and custom kernels for improved model performance

• Design storage and networking architectures optimized for high-throughput ML workloads

• Troubleshoot and resolve complex performance bottlenecks at the GPU driver and kernel level

Customer Engagement & Technical Leadership

• Partner with AWS AI Specialist Solution Architects and customer ML teams to understand model

requirements and deployment constraints

• Provide technical guidance on model selection, fine-tuning strategies, and production best practices

• Conduct performance benchmarking and cost optimization analysis for ML workloads

• Share field insights with AWS product teams to influence infrastructure and service roadmaps

What We're Looking For

Core Qualifications

• Bachelor's degree in computer science, Engineering, or equivalent practical experience (Master's or

PhD preferred)

• 5+ years of experience in machine learning infrastructure, model deployment, or GPU computing

• Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow, JAX)

• Deep understanding of LLM architectures, training methodologies, and inference optimization

Technical Expertise (High-Level Alignment)

• Hands-on experience training, fine-tuning, or deploying large language models in production

• Proficiency with GPU programming, CUDA, and kernel-level optimization techniques

• Experience with distributed training frameworks and multi-GPU/multi-node orchestration

• Strong knowledge of AWS core services: EC2 (GPU instances), S3, EFS, VPC, and networking

Preferred Experience

• Direct experience with Amazon SageMaker AI (Training, Inference, HyperPod) or equivalent ML

platforms

• Understanding of GPU architectures (NVIDIA A100, H100) and AWS custom silicon (Trainium,

Inferentia)

• Experience with model compression techniques (quantization, pruning, distillation)

• Knowledge of MLOps practices, model monitoring, and production ML system design

• Background in high-performance computing, distributed systems, or systems programming

Essential Attributes

• Ability to dive deep into technical problems and debug complex infrastructure issues

• Strong analytical skills with data-driven approach to optimization

• Excellent communication skills to explain complex technical concepts to diverse audiences

• Comfortable working in ambiguous, fast-paced environments with evolving requirements

• Ownership mindset with ability to drive projects from architecture to production

You will be at the forefront of Byteridge's AI infrastructure capabilities, helping customers unlock the full potential of foundation models through expert-level deployment on GPU infrastructure.

This highly technical role requires deep expertise in machine learning infrastructure, GPU optimization, and production ML systems, combined with the ability to translate complex technical concepts into customer success.

What You'll Do

Model Deployment & Optimization

• Lead end-to-end deployments of large language models on AWS infrastructure for strategic

customers

• Design and implement training, fine-tuning, and inference pipelines using Amazon SageMaker AI

• Optimize model performance through GPU-level tuning, kernel optimization, and infrastructure

configuration

• Deploy models on diverse GPU architectures including NVIDIA and AWS custom silicon (Trainium,

Inferentia)

Infrastructure Architecture & Performance

• Architect scalable ML infrastructure using SageMaker AI Inference, HyperPod, and distributed

training frameworks

• Implement CUDA-level optimizations and custom kernels for improved model performance

• Design storage and networking architectures optimized for high-throughput ML workloads

• Troubleshoot and resolve complex performance bottlenecks at the GPU driver and kernel level

Customer Engagement & Technical Leadership

• Partner with AWS AI Specialist Solution Architects and customer ML teams to understand model

requirements and deployment constraints

• Provide technical guidance on model selection, fine-tuning strategies, and production best practices

• Conduct performance benchmarking and cost optimization analysis for ML workloads

• Share field insights with AWS product teams to influence infrastructure and service roadmaps

What We're Looking For

Core Qualifications

• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience (Master's or

PhD preferred)

• 5+ years of experience in machine learning infrastructure, model deployment, or GPU computing

• Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow, JAX)• Deep understanding of LLM architectures, training methodologies, and inference optimization

Technical Expertise (High-Level Alignment)

• Hands-on experience training, fine-tuning, or deploying large language models in production

• Proficiency with GPU programming, CUDA, and kernel-level optimization techniques

• Experience with distributed training frameworks and multi-GPU/multi-node orchestration

• Strong knowledge of AWS core services: EC2 (GPU instances), S3, EFS, VPC, and networking

Preferred Experience

• Direct experience with Amazon SageMaker AI (Training, Inference, HyperPod) or equivalent ML

platforms

• Understanding of GPU architectures (NVIDIA A100, H100) and AWS custom silicon (Trainium,

Inferentia)

• Experience with model compression techniques (quantization, pruning, distillation)

• Knowledge of MLOps practices, model monitoring, and production ML system design

• Background in high-performance computing, distributed systems, or systems programming

Essential Attributes

• Ability to dive deep into technical problems and debug complex infrastructure issues

• Strong analytical skills with data-driven approach to optimization

• Excellent communication skills to explain complex technical concepts to diverse audiences

• Comfortable working in ambiguous, fast-paced environments with evolving requirements

• Ownership mindset with ability to drive projects from architecture to production

About the Role

We are looking for a senior backend engineer to build the infrastructure that powers AI agents in enterprise environments. You will work on systems that securely run, manage, monitor, and govern AI agents as they interact with users, business applications, and external tools.

This role combines backend engineering, distributed systems, AI agent infrastructure, security, and platform development.

Responsibilities

• Build and maintain the core runtime that manages AI agent execution and lifecycle.
• Develop systems for message processing, task orchestration, queue management, and recovery from failures.
• Design secure communication and execution boundaries between AI agents and the host platform.
• Build and enhance sandboxed environments for safe tool and code execution.
• Develop scalable backend services, APIs, and platform components.
• Build admin interfaces and APIs for configuring agents, permissions, approvals, and audits.
• Implement capability, access control, and permission management systems.
• Develop durable memory and state management systems for AI agents.
• Build integrations with communication platforms, business applications, and external systems.
• Improve platform reliability, observability, security, and performance.
• Collaborate closely with engineering teams to design, develop, test, and ship new capabilities.

Required Skills & Experience

• 5+ years of backend software engineering experience.
• Strong proficiency in TypeScript, Node.js, or another modern typed programming language.
• Experience building scalable, distributed, and event-driven systems.
• Strong understanding of databases, transactions, queues, background workers, and system reliability.
• Experience designing and building REST APIs and backend services.
• Hands-on experience using AI coding tools and assistants in daily development workflows.
• Understanding of AI agent frameworks, agent workflows, tool calling, context management, or agent orchestration concepts.
• Strong knowledge of system design, security principles, authentication, authorization, and access control.
• Experience debugging, optimizing, and maintaining production systems.
• Ability to work independently in large codebases and deliver high-quality solutions.

Good to Have

• Experience with AI agent frameworks or SDKs.
• Experience building developer platforms, admin consoles, or management systems.
• Knowledge of sandboxing, process isolation, containers, or secure execution environments.
• Experience with distributed systems concepts such as ordering, retries, idempotency, and fault recovery.
• Experience designing extensible architectures and integration platforms.
• Exposure to AI infrastructure, LLM applications, or autonomous agent systems.

What We're Looking For

• Strong backend engineering fundamentals.
• Security-first mindset.
• Experience building reliable production systems.
• Interest in AI agents and AI infrastructure.
• Ability to move quickly, solve complex technical problems, and work in a fast-paced environment.

Bigdata with cloud:

Experience : 5-10 years

Location : Hyderabad/Chennai

Notice period : 15-20 days Max

1.  Expertise in building AWS Data Engineering pipelines with AWS Glue -> Athena -> Quick sight

2.  Experience in developing lambda functions with AWS Lambda

3.  Expertise with Spark/PySpark – Candidate should be hands on with PySpark code and should be able to do transformations with Spark

4.  Should be able to code in Python and Scala.

5.  Snowflake experience will be a plus

• End-to-end full-stack development experience
• Full hands-on experience with at least one of the following languages Java, PHP, Python, .NET and code repositories like GIT, SVN
• Expertise with HTML5, JQuery, CSS
• Proficiency with front-end JavaScript frameworks like Angular, React, etc.
• Experience of designing and developing APIs in a micro-service architecture
• Experience with webserver technologies like Node.js, J2EE, Apache etc.
• Good understanding and working experience with either relational or non-relational databases like Oracle, MySQL, PostgreSQL, Mongo DB, Cassandra
• Good understanding of the changing trends of user interface guidelines for mobile apps and be able to transform apps to newer form factors
• Hands-on with Native UI Components
• Familiar with Cloud components & deployment procedures.
• Familiar with code repository

Role and Responsibilities

• Making technology work for small holder farmers is the primary function of this team, the individual joining this team should be self-driven towards creating impact.
• A keen listener and has a pro-active approach to problem solving.
• Should understand the role of digital transformation in a company’s journey.
• An individual who follows technological advancements closely and thinks of new and innovative use cases that such technology can solve.
• Having previous experience in product management and/or platform development projects is a plus.
• Knowledge of software development life cycle and software configuration management tools preferred.
• The candidate should demonstrate high bias-for-action and should drive results that matter to the function and to the entire organisation.
• Build from ground up, a scalable server infrastructure and client applications.
• Design, develop and deploy features and consume APIs with high quality standards.
• Manage the infrastructure hosted in the cloud.
• Contribute significantly in reviewing code, design & test-cases authored by peers.

Qualifications and Education Requirements

• 2-6 years experience of design and development experience building scalable & distributed systems.
• Bachelor’s or Master’s degree in Engineering from reputed institutes.

SKILLS

• Agile Project Management
• Software Development Life Cycle and Software Configuration Management
• Excellent coding, debugging skills.
• Hands-on experience on the following tech stacks:
  ReactJs, NodeJs, TypeScript, PostgresSQL/MongoDB, Nginx, Pm2, Redis, Bootstrap, CSS
• Knowledge of Microservices and REST APIs.
• Must have: Experience with managing server infra in hybrid cloud AWS & GCP.
• Must Have: Very good understanding of OOPS and design patterns.
• Nice to have: Hands-on-experience with analytics using ELK stack/ Mixpanel.

• Min 7+ Years of experience as Testing experts
• Test Engineer with 3+ Yrs of experience inTOSCAautomation Tool
• Responsible for planning, designing, deploying, maintenance and troubleshooting related toTOSCA
• Must have a proven experience ofin leading the development of automation framework and automation (functional) test scripts
• Good knowledge and hands one experience inTOSCAautomation Tool
• Execute test automation scripts and Publish test reports
• Design and develop Test Automation Scripts usingTosca
• Holds good knowledge and experience in differentToscarelated automation frameworks