IoT / Edge Gateway Engineer || Indore (on-site)

• Design and implement scalable IoT solutions from sensor to cloud, ensuring seamless integration between

vehicle hardware (fuel sensors, GPS trackers, OBD devices) and the Anytime Diesel platform

• Integrate industrial and automotive sensors, microcontrollers, and gateways with the platform

• Develop, optimize, and troubleshoot data flow using protocols such as CAN bus, Modbus, RS485, TCP, and

RTU

• Manage the full IoT device lifecycle across the fleet — provisioning, remote configuration, health monitoring,

and OTA/FOTA firmware updates

• Collaborate with software, data, and operations teams to define data models and ensure clean data ingestion for

fleet analytics

• Conduct testing, debugging, and performance analysis of embedded firmware and IoT systems using tools like

oscilloscopes and logic analyzers

• Create technical documentation — architecture diagrams, API specs, and deployment guides

Experience: 4–6 Years

Domain: Automotive IoT | Connected Vehicles | Firmware & OTA

Core Stack: Rust | AWS | IoT Core | Apache Kafka | MemoryDB

Key Responsibilities  

OTA & Firmware Lifecycle  

• Co-own OTA firmware rollout operations across multi-ECU connected vehicle architectures.
• Design automated mechanisms to detect update failures, network interruptions, verification errors, and stalled deployments.
• Implement deterministic retry, recovery, and rollback mechanisms to ensure reliable firmware updates without vehicle bricking.
• Ensure firmware package integrity, signature validation, and data security throughout the OTA pipeline.

Data Engineering & Telemetry  

• Design and maintain real-time streaming pipelines for vehicle telemetry, heartbeats, OTA campaign status, and ECU state changes.
• Build high-throughput data services and workers using Rust for payload routing, processing, and verification.
• Use Apache Kafka and AWS IoT Core for real-time data ingestion and event streaming.
• Leverage AWS MemoryDB for Redis for low-latency fleet state, campaign progression, and session management.
• Build resilient pipelines capable of handling intermittent connectivity, noisy networks, and out-of-order data.

Monitoring & Analytics  

• Build real-time dashboards for fleet health, firmware versions, OTA campaigns, and update progress.
• Define and monitor key OTA metrics including success/failure rates, retry rates, failure categories, and completion time.
• Implement automated alerting and anomaly detection for unexpected failure spikes during staged or canary rollouts.
• Analyze logs, traces, and telemetry data to identify campaign bottlenecks, telemetry loss, and hardware-related failures.

Required Skills  

Mandatory  

• 4–6 years of experience in Data Engineering, Software Engineering, or IoT Backend Engineering.
• Strong hands-on experience with Rust for backend/data processing applications.
• Experience with AWS, particularly IoT Core, S3, ECS/EKS, and Lambda.
• Strong experience with Apache Kafka and real-time data pipelines.
• Hands-on experience with AWS MemoryDB for Redis or Redis Enterprise.
• Working knowledge of Python and SQL.
• Experience with MQTT, WebSockets, and HTTP/S protocols.
• Strong understanding of distributed systems, streaming data, and resilient data pipelines.

Preferred  

• Experience with firmware lifecycle management and OTA systems.
• Exposure to connected vehicles, automotive IoT, telemetry platforms, or connected hardware fleets.
• Experience with device shadows and fleet/device state management.
• Experience building telemetry dashboards using Power BI, Apache Superset, or custom dashboards.
• Experience with staged/canary deployments and automated failure recovery.

Primary Technology Stack  

• Languages: Rust, Python, SQL
• Cloud: AWS, IoT Core, S3, ECS/EKS, Lambda
• Streaming: Apache Kafka
• Caching & State: AWS MemoryDB for Redis, Redis
• IoT Protocols: MQTT, WebSockets, HTTP/S
• Analytics & Visualization: Power BI, Apache Superset
• Domain: Automotive IoT, Vehicle Telemetry, OTA, Firmware Management

Technical Lead – Embedded Software Application Projects

link: https://www.ziliconcloud.com/careers

ZILICONCLOUD PRIVATE LIMITED is looking for an experienced Technical Lead with 5–8 years of industry experience in Embedded Systems, IoT, AI, Cloud, and Software Engineering.

The candidate will lead Embedded, IoT, Edge AI, and Cloud projects, define system architecture, convert requirements into technical tasks, and ensure successful project execution and delivery.

Key Responsibilities

• Design modular system architectures for Embedded, IoT, Edge AI, Cloud, REST APIs, and dashboards.
• Convert requirements into clear tasks, milestones, and deliverables.
• Track project progress, manage technical risks, and ensure on-time delivery.
• Guide engineers on coding standards, Git, testing, debugging, and documentation.
• Troubleshoot issues across hardware, firmware, IoT, cloud, backend, and UI.
• Support system integration, testing, debugging, and performance improvement.
• Review technical designs, code, and test results.
• Lead prototype development, integration, technical reviews, and demonstrations.
• Mentor young engineers and explain complex technical concepts in a simple and practical way.
• 
  

Required Skills

C/C++, Python, JavaScript/TypeScript, Linux, FreeRTOS, Microcontrollers, REST APIs, MQTT, Git, Embedded Software, IoT, and system debugging.

Preferred: AWS IoT, Microsoft Azure, ThingsBoard, OpenCV, TensorFlow Lite (TFLite), React, Flutter, or FastAPI.

Education

B.E./B.Tech/M.E./M.Tech in ECE, CSE, Embedded Systems, Mechatronics, or a related field.

📍 Location: East Tambaram, Chennai, Tamil Nadu

💼 Experience: 5–8 Years

🕒 Employment Type: Full-Time

Platform Engineer

Location: Bengaluru, India (Hybrid)

Employment Type: Full-time

Experience: 2-4 years

About Compnay

This is driving the electric mobility revolution through cutting-edge software, infrastructure, and professional services. Our technology empowers utilities, cities, fleets, transit agencies, and automakers to deploy EV charging infrastructure at scale safely, efficiently, and sustainably. With a global footprint spanning three continents and operations in 13 countries, we are passionate about shaping the future of sustainable transport.

Operating over 70,000 charge points globally, this is driving the transition toward cleaner, smarter, and more efficient mobility. The India team serves as a critical operational hub, supporting global platforms focused on decarbonization, digitalization, and scalable infrastructure growth.

Role Overview

What you’ll do:

• Ensure system reliability, uptime, and performance of global platform.
• Conduct real-time surveillance of our EV charging systems to proactively identify and mitigate performance issues and anomalies near 24/7 basis. As such, you collaborate with IDT and FMC players to ensure incident detection also happens outside office hours (monitoring shifts among team members subject to duty schedule).
• Deliver on change & releases like firmware changes and drive insights & intelligence back into testing processes and tech discussions with the wider organization.
• Successfully deliver and project manage first time right commissioning activities alongside our Engineering Procurement Contract Management (EPCM) partners to successfully bring charge points onto our Charge Point Management System (CPMS).
• Provide technical guidance and support to DC specialists during the commissioning of EV charging solutions.
• Work closely with Shell, Engineering, and IT colleagues to ensure projects are completed on time and to specification.
• Act as a liaison with the Engineering Procurement Contract Management (EPCM) partner to manage projects from start to finish, ensuring charge points are successfully onboarded on the Charge Point Management System (CPMS).
• Collaborate with development, operations and support teams to build scalable and resilient systems.
• Contribute to incident response, root-cause analysis, and post-mortem reviews, driving continuous improvement.
• Participate in capacity planning, performance tuning, and resource optimization.
• Integrate security and compliance best practices into all infrastructure operations.
• Stay current with emerging SRE tools, frameworks, and cloud technologies to continuously improve reliability practices.
• Participate in and lead on-call rotations and incident response, conducting detailed postmortems and RCA reports.
• Flexible to resolve blocking issues during off hours or weekends if required.

What We’re Looking For:

Basic Qualifications and Skills

• Bachelor’s degree in Engineering, Electrical, ECE, Computer Science, Information Technology, or related field.
• 2–4 years of overall experience with at least 1+ years of experience as a Site Reliability Engineer, DevOps Engineer, or Technical Project Coordinator.
• Proven experience of DevOps, SRE or Technical Project Coordination with IoT or connected devices-based platforms.
• Experience with incident management and on-call best practices. Provide support to on-call engineers.
• Excellent analytical and problem-solving skills with a proactive mindset.
• Expertise with monitoring and observability tools (Dynatrace, Prometheus, Grafana, Zabbix, etc.).
• Solid understanding of cloud platforms (AWS) and AWS native services (EKS, EC2, S3, RDS, Lambda).
• Proactively monitor the network, triage performance outliers, and coordinate correction actions to ensure optimal system functionality.
• Fluency in English (spoken and written).
• Successfully recommission or decommission chargers following changes in our network.
• Responsible for the go-live of the chargers on Shell’s public network following commissioning attempts.

Additional Information

• This role involves managing infrastructure for a global platform operating in over ten countries, requiring effective communication and collaboration across regions.
• Strong verbal and written communication skills, along with availability and flexibility to resolve blocking issues, are essential to support on-call engineers.
• This role may involve EU or US time-zone shifts based on business requirements.
• Shift timing: 2 PM IST to 11 PM IST.

What is required to be successful in this role:

• Global platform experience (B2C or B2B).
• AWS native service experience.
• Firmware deployment and cloud cost optimization experience.
• Strong exposure to monitoring and alerts.
• Experience with firmware rollout, IoT devices onboarding and offboarding will be an added advantage.
• Experience as an SRE or DevOps Engineer with some exposure to Project Management or Technical Project Management in IoT-based projects will be helpful.  

What We Offer

• Work with some of the brightest minds in the emerging EV industry.
• Make a tangible impact in reducing carbon emissions and enabling sustainable energy.
• Freedom to suggest, implement, and innovate on systems, processes, and technologies.
• Daily ownership in a high-growth, challenging environment.
• Flexible work environment with hybrid schedules and virtualization options.
• Competitive pay and benefits including health coverage, innovative PTO program, and performance bonuses.

Job Title: Software/Hardware Engineer (IIT/NIT)

Location: Bangalore

Website: https://www.zeuron.ai

Experience: 1 Year

CTC: 6-7 LPA

About the Company

Zeuron.ai is a Bangalore-based deep-tech startup founded in 2019, focused on building brain-inspired computing and AI-driven healthcare solutions. The company combines neuroscience, AI, and gaming to create innovative digital therapeutics and neurotechnology platforms for improving brain health, rehabilitation, and overall well-being.

About the Role

We are looking for a highly motivated Software/Hardware Engineer from premier institutes (IIT/NIT) with strong fundamentals and a passion for building scalable and efficient systems. This role offers an opportunity to work on cutting-edge technology and solve real-world problems.

Key Responsibilities

Design, develop, and optimize software/hardware solutions

Work on system architecture, debugging, and performance improvements

Collaborate with cross-functional teams (product, design, operations)

Participate in code reviews, testing, and deployment processes

Contribute to innovation and continuous improvement initiatives

Requirements

B.Tech/M.Tech from IITs/NITs (Computer Science, Electronics, Electrical, or related fields)

1 year of experience (internships/project experience considered)

Strong programming skills (C/C++/Python/Java) or hardware fundamentals (embedded systems, VLSI, circuit design)

Good understanding of data structures, algorithms, and system design

Problem-solving mindset with strong analytical skills

Preferred Skills

Experience with embedded systems, IoT, or product development

Knowledge of cloud platforms or system-level programming

Good in Computer vision, Flutter, JavaScript, AI/ML

About Jinn

Jinn is a Voice AI Tech Company. It helps businesses get better RoI specially by helping sales processes with the use of Voice AI Tech. We are adding a business line which includes an audio device that can reliably capture audio in various environments.

About role:

• This Role in a B2B SaaS startup in AI space led by 2X entrepreneurs from IIT, IIMs. Fast paced with a lot of learning and growth.
• Responsibility: Helping engineer/assemble/bring together an IoT/ hardware device that can accomplish product goals with required constraints. Great high stakes exposure for fresh grads
• Duration: 3-6 months internship || Converts to Full Time based on performance 
• Compensation (Stipend): 20-25k per month || Full time 4.5lpa - 6LPA

Ideal Profile: Interested in building a career in IoT/Tech, good communication, good discipline, solid understand of tech (AI)

Skill Sets

Look for someone who:

•⁠ ⁠Has built at least 1 IoT project end-to-end

•⁠ ⁠Knows Arduino + one of ESP32 / nRF52

•⁠ ⁠Has touched audio input (even basic)

•⁠ ⁠Is comfortable debugging hardware (this is key)

1.⁠ ⁠Embedded Systems Programming (Must-have)

•⁠ ⁠C/C++ (Arduino framework or ESP-IDF)

•⁠ ⁠Working with:

  * ESP32 OR

  * Seeed Studio XIAO BLE nRF52840 Sense

•⁠ ⁠Skills:

  * GPIO, I2S (for mic input)

  * Power modes (deep sleep, wake triggers)

  * Memory constraints (huge in audio use cases)

👉 This is the backbone. If they can’t do this well, project stalls.

2.⁠ ⁠Audio Handling + Signal Basics

•⁠ ⁠Understanding:

  * Sampling rate (16kHz vs 44.1kHz)

  * PCM audio buffers

  * Latency vs quality trade-offs

•⁠ ⁠Practical skills:

  * Using I2S microphones (INMP441, etc.)

  * Basic noise filtering

  * Voice Activity Detection (VAD)

👉 Without this, you’ll just get noisy unusable recordings.

3.⁠ ⁠Power & Hardware Basics (Often underestimated)

•⁠ ⁠LiPo battery handling

•⁠ ⁠Charging IC (TP4056 type)

•⁠ ⁠Power optimization:

  * Sleep modes

  * Sampling intervals

Many prototypes fail here (battery drains in 1 hour 😅)

4.⁠ ⁠Connectivity (BLE / WiFi)

•⁠ ⁠BLE (for XIAO nRF52840):

  * Data chunking (BLE MTU limits!)

  * Pairing + mobile relay model

•⁠ ⁠WiFi (for ESP32):

  * HTTP / WebSocket streaming

  * Retry + buffering

Trade

Job Description – Embedded Application Engineer (4–6 Years Experience)

Position

Embedded Application Engineer

Experience

4–6 Years

Location

Hyderabad

Job Summary

We are seeking a highly motivated Embedded Application Engineer with 4–6 years of experience in developing, deploying, and maintaining embedded software applications on Linux-based platforms. The ideal candidate should possess strong programming skills in Go, C/C++, Linux, and Python, leverage modern AI-assisted development tools such as Cursor, and have experience working with industrial communication protocols, messaging systems, and DevOps automation pipelines.

The role involves designing edge applications, integrating industrial devices, implementing secure communication frameworks, and enabling scalable deployment and lifecycle management across ARM and AMD-based hardware platforms.

Key Responsibilities

· Design, develop, and maintain embedded applications for Linux-based edge devices.

· Develop high-performance software components using Go, C/C++, Linux, and Python.

· Utilize AI-powered coding assistants (e.g., Cursor) to improve development productivity and code quality.

· Implement and integrate communication protocols such as:

o MQTT

o Sparkplug B

o JSON-based messaging interfaces

o Industrial protocols (Modbus preferred)

· Build edge-to-cloud data communication services and telemetry pipelines.

· Develop software for ARM and AMD processor architectures.

· Create automated CI/CD pipelines using CircleCI and related DevOps tools.

· Implement automated testing, deployment, and release processes.

· Perform debugging, profiling, and performance optimization for embedded systems.

· Collaborate with product, cloud, and platform engineering teams to deliver scalable and secure solutions.

· Support software configuration, packaging, deployment, and version management.

· Contribute to system monitoring, diagnostics, and fleet lifecycle management.

Required Skills & Qualifications

Programming Languages

· Strong proficiency in:

o Go

o C/C++

o Python

o Linux Application development

· Experience using AI-assisted coding tools such as Cursor or similar developer productivity tools.

Embedded & Platform Expertise

· Strong experience with:

o Linux-based embedded development

o Application-level debugging

o ARM and AMD processor architectures

o Multi-threaded and concurrent application design

Communication & Protocols

· Hands-on experience with:

o MQTT

o Sparkplug B

o JSON message structures and APIs

· Familiarity with industrial communication protocols:

o Modbus (preferred)

DevOps & Automation

· Experience with:

o CircleCI

o Continuous Integration (CI)

o Continuous Delivery/Deployment (CD)

o Automated testing frameworks

o Version control systems (Git)

Device & Fleet Management

· Experience with:

o Software packaging and deployment

o Remote device management

o Fleet monitoring and maintenance

o Canonical Snap package management

Preferred Qualifications

· Experience in IoT, Edge Computing, Building Automation, Industrial Automation, or HVAC domains.

· Familiarity with container technologies (Docker/Podman).

· Understanding of cybersecurity practices for embedded devices.

· Experience with cloud integration (AWS, Azure, or GCP).

· Knowledge of telemetry, diagnostics, and remote software update mechanisms.

Key Competencies

· Strong problem-solving and debugging skills.

· Excellent communication and collaboration abilities.

· Ability to work independently in agile development environments.

· Focus on software quality, maintainability, and reliability.

· Passion for automation and modern software engineering practices.

Nice-to-Have Domain Experience

· IoT Edge Platforms

· Industrial Automation Systems

· Building Management Systems (BMS)

· HVAC Controls and Equipment Connectivity

· Smart Building and Energy Management Solutions

Experience Range: 4–6 Years

Education: Bachelor's or Master's degree in Computer Science, Electronics, Electrical Engineering, Embedded Systems, or a related field.

About the Internship

Nexora Group is seeking enthusiastic students interested in the Internet of Things (IoT) and Embedded Systems. This internship provides hands-on exposure to smart devices, sensor integration, microcontrollers, embedded programming, and IoT-based applications.

Interns will gain practical experience working on real-world projects involving connected devices, automation systems, data collection, and intelligent monitoring solutions while learning industry-relevant technologies.

Key Responsibilities

• Assist in the development of IoT and Embedded Systems projects.
• Work with sensors, microcontrollers, and hardware components.
• Develop and test embedded applications.
• Collect, monitor, and analyze data from IoT devices.
• Support system integration and troubleshooting activities.
• Create technical documentation and project reports.
• Participate in project discussions and team meetings.
• Research emerging IoT and embedded technologies.

Required Skills

• Basic understanding of Electronics and Embedded Systems.
• Familiarity with Arduino, ESP32, Raspberry Pi, or similar platforms.
• Basic knowledge of C, C++, or Python programming.
• Understanding of sensors, actuators, and communication protocols.
• Strong analytical and problem-solving skills.
• Passion for innovation and technology.

Eligibility

• B.Tech, M.Tech, Diploma, B.Sc., M.Sc., or related disciplines.
• Students pursuing Electronics, Electrical Engineering, Embedded Systems, IoT, Computer Science, Instrumentation, Mechatronics, or related fields.
• Freshers and recent graduates are encouraged to apply.

What You Will Learn

✅ Internet of Things (IoT) Fundamentals

✅ Embedded Systems Development

✅ Microcontroller Programming

✅ Sensor & Device Integration

✅ IoT Communication Protocols

✅ Smart Automation Systems

✅ Industry-Oriented Project Development

Benefits

✅ Internship Completion Certificate

✅ Letter of Recommendation (Performance-Based)

✅ Hands-on Industry Project Experience

✅ Professional Mentorship & Guidance

✅ Resume & LinkedIn Profile Enhancement

✅ Portfolio Development Support

✅ Exposure to Real-World IoT Applications

Build smart energy solutions combining IoT sensors, edge computing, and real-time analytics.

What you'll do:

• Develop solar panel monitoring systems (Raspberry Pi/ESP32)
• Implement MQTT brokers and time-series databases (InfluxDB)
• Create energy optimization algorithms (ML-based forecasting)
• Build dashboards (Grafana, custom React apps)
• Deploy edge AI models for predictive maintenance
• Integrate with smart grid protocols

What we need:

• Python, basic electronics
• Arduino/ESP32 projects
• Interest in renewable energy/IoT
• Cloud basics (MQTT, AWS IoT Core)

Impact:

• Systems deployed at 50+ solar installations
• Green tech portfolio for sustainability roles
• Patent publication opportunity

GEMBA CONCEPTS

Experience: ~3–5 years Type: Full-time

AI/ML Engineer

Location: Bengaluru, India (Hybrid)

About Gemba Concepts

Gemba Concepts is a lean manufacturing and technology consulting firm helping clients across pharma, manufacturing, and logistics

modernize how they operate. We build production systems that sit close to the shop floor — warehouse management, manufacturing

traceability, and an applied AI/ML platform whose flagship use cases are visual quality inspection and predictive maintenance. We’re a

tight engineering team that ships real systems for demanding, often regulated, environments.

The Role

We’re looking for an AI/ML Engineer to take ML capabilities from prototype to production. You’ll own models end-to-end — framing the

problem with stakeholders, building and validating the model, and deploying it as a reliable service that holds up against real-world, messy

industrial data. This is a hands-on building role, not a pure research seat: your work goes into client-facing systems.

What You’ll Do

Build and ship computer vision models for visual quality inspection (defect detection, classification, segmentation) that perform under

real factory lighting, throughput, and edge-case conditions.

Develop predictive maintenance models using sensor/time-series data — anomaly detection, remaining-useful-life estimation, failure

prediction.

Own the full ML lifecycle: data pipelines, feature engineering, training, evaluation, and deployment, with proper versioning and monitoring.

Deploy and serve models in production on Azure (AKS), and keep them healthy — track drift, retraining triggers, and latency.

Integrate LLM-based capabilities (we use the Claude API and self-hosted open models) into delivery and product workflows where they

add leverage.

Collaborate with product, engineering, and domain experts to translate fuzzy operational problems into well-scoped ML solutions — and to

know when ML is not the right answer.

Communicate results and limitations clearly to non-ML stakeholders, including clients.

What We’re Looking For

3–5 years of hands-on experience building and deploying ML models in production (not just notebooks or coursework).

Strong Python and the modern ML stack — PyTorch or TensorFlow, scikit-learn, NumPy/Pandas.

Solid grounding in at least one of: computer vision (CNNs, object detection/segmentation, image preprocessing) or time-series /

anomaly detection.

Practical MLOps experience: containerization (Docker), model serving, experiment tracking, and deploying on a cloud platform — Azure /

Kubernetes (AKS) is a strong plus.

Comfort working with imperfect, real-world data — labeling strategy, class imbalance, data drift, and validation that reflects production

reality.

Good engineering hygiene (Git, testing, code review) and the ability to write code others can build on.

Nice to Have

Experience with industrial / manufacturing data or regulated environments (pharma, 21 CFR Part 11 awareness).

Hands-on LLM integration experience — RAG, prompt engineering, working with APIs or self-hosted models (vLLM, Qwen, etc.).

Edge deployment experience (running CV models on-device / near the line).

Exposure to data pipeline tooling and orchestration.

What You’ll Get

Real ownership of ML systems that go into production for serious clients.

A lean, senior-heavy team where you ship fast and learn across the stack.

Direct exposure to applied AI in manufacturing — a domain where the work has tangible, physical impact