20 Lora Jobs

Company Name - Fission Labs Apply Here - https://app.fabrichq.ai/jobs/0e46cebe-8b91-4a96-9061-950b66dc4d54 About Us: Headquartered in Sunnyvale, with offices in Dallas & Hyderabad, Fission Labs is a leading software development company, specializing in crafting flexible, agile, and scalable solutions that propel businesses forward.With a comprehensive range of services, including product development, cloud engineering, big data analytics, QA, DevOps consulting, and AI/ML solutions, we empower clients to achieve sustainable digital transformation that aligns seamlessly with their business goals. Key Responsibilities Design and architect complex Generative AI solutions using AWS technologies Develop advanced AI architectures incorporating state-of-the-art GenAI technologies Create and implement Retrieval Augmented Generation (RAG) and GraphRAG solutions Architect scalable AI systems using AWS Bedrock and SageMaker Design and implement agentic AI systems with advanced reasoning capabilities Develop custom AI solutions leveraging vector databases and advanced machine learning techniques Evaluate and integrate emerging GenAI technologies and methodologies Technical Expertise Requirements Generative AI Technologies Expert-level understanding of: Retrieval Augmented Generation (RAG) Vector Database architectures Agentic AI design principles AWS AI Services Comprehensive expertise in: AWS Bedrock Amazon SageMaker AWS AI/ML services ecosystem Cloud-native AI solution design Technical Skills Advanced Python programming for AI/ML applications

Conceptualize, design, and produce engaging and high-quality videos using AI video generation tools like InVideo AI, Runway ML, Kling AI, and other relevant software.A strong portfolio showcasing your AI-generated video work is essential.

Roles and Responsibilities: As a, Associate Manager - Senior Data scientist you will solve some of the most impactful business problems for our clients using a variety of AI and ML technologies. You will collaborate with business partners and domain experts to design and develop innovative solutions on the data to achieve predefined outcomes. - Engage with clients to understand current and future business goals and translate business problems into analytical frameworks - Develop custom models based on in-depth understanding of underlying data, data structures, and business problems to ensure deliverables meet client needs - Create repeatable, interpretable and scalable models - Effectively communicate the analytics approach and insights to a larger business audience - Collaborate with team members, peers and leadership at Tredence and client companies Qualification: - Bachelor's or Master's degree in a quantitative field (CS, machine learning, mathematics, statistics) or equivalent experience. - 5+ years of experience in data science, building hands-on ML models - Experience with LMs (Llama (1/2/3), T5, Falcon, Langchain or framework similar like Langchain) - Candidate must be aware of entire evolution history of NLP (Traditional Language Models to Modern Large Language Models), training data creation, training set-up and finetuning - Candidate must be comfortable interpreting research papers and architecture diagrams of Language Models - Candidate must be comfortable with LORA, RAG, Instruct fine-tuning, Quantization, etc. - Experience leading the end-to-end design, development, and deployment of predictive modeling solutions. - Excellent programming skills in Python. Strong working knowledge of Python's numerical, data analysis, or AI frameworks such as NumPy, Pandas, Scikit-learn, Jupyter, etc. - Advanced SQL skills with SQL Server and Spark experience. - Knowledge of predictive/prescriptive analytics including Machine Learning algorithms (Supervised and Unsupervised) and deep learning algorithms and Artificial Neural Networks - Experience with Natural Language Processing (NLTK) and text analytics for information extraction, parsing and topic modeling. - Excellent verbal and written communication. Strong troubleshooting and problem-solving skills. Thrive in a fast-paced, innovative environment - Experience with data visualization tools -- PowerBI, Tableau, R Shiny, etc. preferred - Experience with cloud platforms such as Azure, AWS is preferred but not required. Required Skills g, Pyspark, Python, SQL, GenAi, NLP, Clasical ML, DL, Supervised ML, Transformer Models, Transformers, Unsupervised ML

Job Description: Graduate degree in a quantitative field (CS, statistics, applied mathematics, machine learning, or related discipline) - Good programming skills in Python with strong working knowledge of Python's numerical, data analysis, or AI frameworks such as NumPy, Pandas, Scikit-learn, etc. - Experience with LMs (Llama (1/2/3), T5, Falcon, Langchain or framework similar like Langchain) - Candidate must be aware of entire evolution history of NLP (Traditional Language Models to Modern Large Language Models), training data creation, training set-up and finetuning - Candidate must be comfortable interpreting research papers and architecture diagrams of Language Models - Candidate must be comfortable with LORA, RAG, Instruct fine-tuning, Quantization, etc. - Predictive modelling experience in Python (Time Series/ Multivariable/ Causal) - Experience applying various machine learning techniques and understanding the key parameters that affect their performance - Experience of building systems that capture and utilize large data sets to quantify performance via metrics or KPIs - Excellent verbal and written communication - Comfortable working in a dynamic, fast-paced, innovative environment with several ongoing concurrent projects. Roles & Responsibilities: - Lead a team of Data Engineers, Analysts and Data scientists to carry out following activities: - Connect with internal / external POC to understand the business requirements - Coordinate with right POC to gather all relevant data artifacts, anecdotes, and hypothesis - Create project plan and sprints for milestones / deliverables - Spin VM, create and optimize clusters for Data Science workflows - Create data pipelines to ingest data effectively - Assure the quality of data with proactive checks and resolve the gaps - Carry out EDA, Feature Engineering & Define performance metrics prior to run relevant ML/DL algorithms - Research whether similar solutions have been already developed before building ML models - Create optimized data models to query relevant data efficiently - Run relevant ML / DL algorithms for business goal seek - Optimize and validate these ML / DL models to scale - Create light applications, simulators, and scenario builders to help business consume the end outputs - Create test cases and test the codes pre-production for possible bugs and resolve these bugs proactively - Integrate and operationalize the models in client ecosystem - Document project artifacts and log failures and exceptions. - Measure, articulate impact of DS projects on business metrics and finetune the workflow based on feedbacks Required Skills g, Pyspark, Python, SQL, GenAi, NLP, Casical ML, DL, Supervised ML, Transformer Models, Transformers, Unsupervised ML

Job Description: Graduate degree in a quantitative field (CS, statistics, applied mathematics, machine learning, or related discipline) Good programming skills in Python with strong working knowledge of Python's numerical, data analysis, or AI frameworks such as NumPy, Pandas, Scikit-learn, etc. Experience with LMs (Llama (1/2/3), T5, Falcon, Langchain or framework similar like Langchain) Candidate must be aware of entire evolution history of NLP (Traditional Language Models to Modern Large Language Models), training data creation, training set-up and finetuning Candidate must be comfortable interpreting research papers and architecture diagrams of Language Models Candidate must be comfortable with LORA, RAG, Instruct fine-tuning, Quantization, etc. Predictive modelling experience in Python (Time Series/ Multivariable/ Causal) Experience applying various machine learning techniques and understanding the key parameters that affect their performance Experience of building systems that capture and utilize large data sets to quantify performance via metrics or KPIs Excellent verbal and written communication Comfortable working in a dynamic, fast-paced, innovative environment with several ongoing concurrent projects. Roles & Responsibilities: Lead a team of Data Engineers, Analysts and Data scientists to carry out following activities: Connect with internal / external POC to understand the business requirements Coordinate with right POC to gather all relevant data artifacts, anecdotes, and hypothesis Create project plan and sprints for milestones / deliverables Spin VM, create and optimize clusters for Data Science workflows Create data pipelines to ingest data effectively Assure the quality of data with proactive checks and resolve the gaps Carry out EDA, Feature Engineering & Define performance metrics prior to run relevant ML/DL algorithms Research whether similar solutions have been already developed before building ML models Create optimized data models to query relevant data efficiently Run relevant ML / DL algorithms for business goal seek Optimize and validate these ML / DL models to scale Create light applications, simulators, and scenario builders to help business consume the end outputs Create test cases and test the codes pre-production for possible bugs and resolve these bugs proactively Integrate and operationalize the models in client ecosystem Document project artifacts and log failures and exceptions. Measure, articulate impact of DS projects on business metrics and finetune the workflow based on feedbacks Required Skills g, Pyspark, Python, SQL, Supervised ML, Transformer Models, Transformers, Unsupervised ML, GenAi

Dear Candidate, We are hiring an IoT Engineer to build and deploy connected devices and edge computing solutions. Ideal for engineers with a strong background in hardware-software integration. Key Responsibilities: Design and develop IoT device software and cloud integrations Implement communication protocols (MQTT, CoAP, BLE) Ensure security, performance, and scalability of IoT ecosystems Work with sensors, gateways, and embedded platforms Required Skills & Qualifications: Proficiency in C/C++, Python, or JavaScript Experience with IoT platforms (AWS IoT, Azure IoT Hub, Google IoT Core) Familiarity with edge computing and real-time systems Bonus: Knowledge of LPWAN, Zigbee, or industrial IoT (IIoT) Soft Skills: Strong troubleshooting and problem-solving skills. Ability to work independently and in a team. Excellent communication and documentation skills. Note: If interested, please share your updated resume and preferred time for a discussion. If shortlisted, our HR team will contact you. Kandi Srinivasa Reddy Delivery Manager Integra Technologies

Job Summary: As the Embedded Engineering Manager, you will lead the development and delivery of embedded firmware and hardware solutions for our IoT products. You will work closely with cross-functional teams including hardware, cloud, mobile, and product management to drive high-quality, scalable, and secure embedded solutions from concept through production. Key Responsibilities: Lead a team of embedded software and firmware engineers through the full product lifecycle. Architect, design, and review embedded system software and firmware for IoT devices. Collaborate with hardware engineers to integrate and validate system-level performance. Ensure secure, scalable, and power-efficient designs in accordance with IoT best practices. Define project roadmaps, allocate resources, and manage timelines and deliverables. Drive best practices for coding standards, testing, CI/CD, and code reviews. Identify and mitigate technical risks and resolve complex engineering challenges. Work closely with QA to develop and implement test strategies (unit, integration, system). Stay abreast of industry trends and new technologies to influence design decisions. Mentor, coach, and grow the embedded engineering team. Qualifications: Required: Bachelors or master’s degree in electrical engineering, Computer Engineering, or related field. 8+ years of experience in embedded systems development with at least 2–3 years in a leadership or management role. Strong proficiency in C/C++, RTOS, and embedded Linux environments. Experience with microcontrollers (ARM Cortex-M, etc.) and SoC platforms. Familiarity with communication protocols: BLE, Wi-Fi, MQTT, Zigbee, LoRa, etc. Solid understanding of secure coding practices and embedded security (e.g., secure boot, encryption). Experience in IoT product development from prototype to production. Strong interpersonal and communication skills. Preferred: Experience working with cloud-connected devices (AWS IoT, Azure IoT, etc.). Knowledge of hardware debugging tools (oscilloscopes, logic analyzers, JTAG). Familiarity with regulatory compliance (e.g., FCC, CE) and certifications. Agile/Scrum experience and familiarity with tools like Jira, Git, Jenkins.

Skilled IoT Developer with experience in embedded systems, expertise in C/C++ programming and Arduino-based development and testing. You will work closely with our R&D teams to build and deploy IoT automation systems for petrol pumps.

Preferred candidate profile 1. LLM Basics : (Llama, Gemini ) : Understand the basics of generative AI and LLMs, such as key terminology, uses, potential issues, and primary frameworks. One should know what the data is trained on and any potential biases/issues that there may be with the data . Knowledge on know exactly how big LLMs can be, how computationally expensive training will be, and the differences between training LLMs and machine learning models. 1. Prompt Engineering : Knowledge on designing inputs for LLMs once theyre developed. 2. Prompt Engineering with OpenAI : As a leading figure in LLMs and generative AI, it’s important to know how to use prompt engineering specifically with OpenAI tools, as you’ll likely be using them at some point in your career. 3. Question-Answering :Question-answering (QA) LLMs are a type of large language model that has been trained specifically to answer questions. 4. Fine-Tuning : Knowledge on Fine-tuning to improve the performance of an LLM on a variety of tasks, including text generation, translation, summarization, and question-answering. Customize LLMs for specific applications, such as customer service chatbots or medical diagnosis systems. Awareness on supervised learning. This involves providing the LLM with a dataset of labelled data, where each data point is a pair of input and output.. 1. Lang Chain : To architect complex LLM pipelines by chaining multiple models together (Classification, text generation, code generation, etc.)`Agents` to interact with all these external systems to execute actions dictated by LLMs. 2. Parameter Efficiency/Tuning : LORA 3. RAG Building : Generative AI, mastering RAG building—short for Retrieval-Augmented Generation—is becoming increasingly crucial 4. ML OPS and in particular LLMOps : Large Language Model Operations, is the practice of managing and maintaining large language models (LLMs) in a production setting 5. TensorFlow i s like a versatile toolbox for creating intelligent programs that can learn and understand various concepts, including machine learning, deep learning, and data science

Role Purpose The purpose of this role is to design, test and maintain software programs for operating systems or applications which needs to be deployed at a client end and ensure its meet 100% quality assurance parameters Machine Learning & Deep Learning – Strong understanding of LLM architectures, transformers, and fine-tuning techniques. MLOps & DevOps – Experience with CI/CD pipelines, model deployment, and monitoring. Vector Databases – Knowledge of storing and retrieving embeddings efficiently. Prompt Engineering – Ability to craft effective prompts for optimal model responses. Retrieval-Augmented Generation (RAG) – Implementing techniques to enhance LLM outputs with external knowledge. Cloud Platforms – Familiarity with AWS, Azure, or GCP for scalable deployments. Containerization & Orchestration – Using Docker and Kubernetes for model deployment. Observability & Monitoring – Tracking model performance, latency, and drift. Security & Ethics – Ensuring responsible AI practices and data privacy. Programming Skills – Strong proficiency in Python, SQL, and API development. Knowledge of Open-Source LLMs – Familiarity with models like LLaMA, Falcon, and Mistral. Fine-Tuning & Optimization – Experience with LoRA, quantization, and efficient training techniques. LLM Frameworks – Hands-on experience with Hugging Face, LangChain, or OpenAI APIs. Data Engineering – Understanding of ETL pipelines and data preprocessing. Microservices Architecture – Ability to design scalable AI-powered applications. Explainability & Interpretability – Techniques for understanding and debugging LLM outputs. Graph Databases – Knowledge of Neo4j or similar technologies for complex data relationships. Collaboration & Communication – Ability to work with cross-functional teams and explain technical concepts clearly. Deliver No. Performance Parameter Measure 1. Continuous Integration, Deployment & Monitoring of Software 100% error free on boarding & implementation, throughput %, Adherence to the schedule/ release plan 2. Quality & CSAT On-Time Delivery, Manage software, Troubleshoot queries, Customer experience, completion of assigned certifications for skill upgradation 3. MIS & Reporting 100% on time MIS & report generation Mandatory Skills: LLM Ops. Experience3-5 Years.

Senior Technical Architect Machine Learning Solutions We are looking for a Senior Technical Architect with deep expertise in Machine Learning (ML), Artificial Intelligence (AI) , and scalable ML system design . This role will focus on leading the end-to-end architecture of advanced ML-driven platforms, delivering impactful, production-grade AI solutions across the enterprise. Key Responsibilities Lead the architecture and design of enterprise-grade ML platforms , including data pipelines, model training pipelines, model inference services, and monitoring frameworks. Architect and optimize ML lifecycle management systems (MLOps) to support scalable, reproducible, and secure deployment of ML models in production. Design and implement retrieval-augmented generation (RAG) systems, vector databases , semantic search , and LLM orchestration frameworks (e.g., LangChain, Autogen). Define and enforce best practices in model development, versioning, CI/CD pipelines , model drift detection, retraining, and rollback mechanisms. Build robust pipelines for data ingestion, preprocessing, feature engineering , and model training at scale , using batch and real-time streaming architectures. Architect multi-modal ML solutions involving NLP, computer vision, time-series, or structured data use cases. Collaborate with data scientists, ML engineers, DevOps, and product teams to convert research prototypes into scalable production services . Implement observability for ML models including custom metrics, performance monitoring, and explainability (XAI) tooling. Evaluate and integrate third-party LLMs (e.g., OpenAI, Claude, Cohere) or open-source models (e.g., LLaMA, Mistral) as part of intelligent application design. Create architectural blueprints and reference implementations for LLM APIs, model hosting, fine-tuning, and embedding pipelines . Guide the selection of compute frameworks (GPUs, TPUs), model serving frameworks (e.g., TorchServe, Triton, BentoML) , and scalable inference strategies (batch, real-time, streaming). Drive AI governance and responsible AI practices including auditability, compliance, bias mitigation, and data protection. Stay up to date on the latest developments in ML frameworks, foundation models, model compression, distillation, and efficient inference . 14. Ability to coach and lead technical teams , fostering growth, knowledge sharing, and technical excellence in AI/ML domains. Experience managing the technical roadmap for AI-powered products , documentations ensuring timely delivery, performance optimization, and stakeholder alignment. Required Qualifications Bachelors or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field. 8+ years of experience in software architecture , with 5+ years focused specifically on machine learning systems and 2 years in leading team. Proven expertise in designing and deploying ML systems at scale , across cloud and hybrid environments. Strong hands-on experience with ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face, Scikit-learn). Experience with vector databases (e.g., FAISS, Pinecone, Weaviate, Qdrant) and embedding models (e.g., SBERT, OpenAI, Cohere). Demonstrated proficiency in MLOps tools and platforms : MLflow, Kubeflow, SageMaker, Vertex AI, DataBricks, Airflow, etc. In-depth knowledge of cloud AI/ML services on AWS, Azure, or GCP – including certification(s) in one or more platforms. Experience with containerization and orchestration (Docker, Kubernetes) for model packaging and deployment. Ability to design LLM-based systems , including hybrid models (open-source + proprietary), fine-tuning strategies, and prompt engineering. Solid understanding of security, compliance , and AI risk management in ML deployments. Preferred Skills Experience with AutoML , hyperparameter tuning, model selection, and experiment tracking. Knowledge of LLM tuning techniques : LoRA, PEFT, quantization, distillation, and RLHF. Knowledge of privacy-preserving ML techniques , federated learning, and homomorphic encryption Familiarity with zero-shot, few-shot learning , and retrieval-enhanced inference pipelines. Contributions to open-source ML tools or libraries. Experience deploying AI copilots, agents, or assistants using orchestration frameworks.

Role & Responsibilities - Microcontroller Programmer Firmware Development: Write and maintain firmware for microcontrollers like ATmega, ESP32, PIC, , ensuring efficient, optimized, and reliable code. Programming & Debugging: Develop code in languages such as C or C++, microcontrollers, and perform debugging using IDEs, logic analyzers, oscilloscopes, and other tools. System Integration: Integrate microcontroller-based systems with sensors, actuators, displays, and communication modules like IoT modules (Wi-Fi, Bluetooth, GSM, LoRa). Testing & Validation: Test and validate firmware performance in real-world conditions, including stress testing, and troubleshoot hardware-software interactions. Documentation: Maintain clear and comprehensive documentation of firmware and hardware design for internal and customer use. Collaboration: Work closely with hardware engineers, software developers, and other team members to develop innovative electronic products. Continuous Improvement: Research and implement new technologies, methodologies, and best practices in embedded system development. Preferred Candidate Profile Educational Background: Bachelors degree in Electronics Engineering, Computer Science, or Diploma in relative field. Experience: 1-4 years of hands-on experience in embedded systems programming, especially with microcontrollers (ATmega, ESP32, ). Technical Skills: Proficiency in C/C++ for embedded systems. Familiarity with RTOS and low-power designs. Experience with communication protocols such as SPI, I2C, UART, and CAN. Knowledge of hardware components like sensors, actuators, and displays. Problem-Solving Skills: Strong analytical and troubleshooting skills to solve hardware-software integration issues. Attention to Detail: Good in coding, testing, and documentation. Team Player: Good communication skills and ability to work in a cross-functional team. Adaptability: Ability to quickly learn new platforms, tools, and technologies. Perks and Benefits Mobile Phone Allowance Travelling Allowance Medical Leaves ( Proof Required) Over Time Incentives

Job description We are seeking a skilled and experienced Data Scientist to join our dynamic team. As Data Scientist, you will play a critical role in driving high-impact data science projects. Responsibilities: Develop and implement advanced machine learning and deep learning models for Data processing, natural language processing, computer vision. Machine Learning lifecycle: data prep, training data generation, feature engineering, optimization, experimentation, reproducibility, deployment, and end-to-end workflow management Knowledge of statistical programming languages like Python, Pandas, Numpy etc. Basic knowledge of query language like SQL. Utilize expertise in statistics, ML to extract valuable insights from complex data sets. Should have knowledge working with libraries like TensorFlow, PyTorch, scikit-learn, NLTK etc. Proven experience in Generative AI. Proven track record of successfully delivering complex data science projects. Work collaboratively with cross-functional teams to identify data science opportunities and provide innovative solutions. Deploy data science models in the form of APIs on Azure Kubernetes Service (AKS) to ensure smooth integration with existing systems. Stay updated with the latest advancements in data science, AI, and related fields, and apply them to enhance our capabilities. Qualifications: Bachelor's or Master' degree 10+ years of industry experience in data science, with a strong background in data processing, deep learning, natural language processing and generation, computer vision and statistics.

Embedded development in Embedded C for various Micro-controllers like MSP430, AVR, ARM, STM series micro-controller using IDEs MPLAB, CCS, KEIL, HITECH, STMcube etc. BE /M.Sc in Electronics /Instrumentation /Computer Exp. Min 5 Years Location :- Pune

8-10 years of exp in IoT development, with knowledge of IoT platforms, protocols, and best practices.Integrate devices with cloud AWS IoT, Azure IoT Hub, or Google Cloud IoT. IoT communication protocols (MQTT, HTTP/HTTPS, Zigbee, Z-Wave, LoRaWAN,

Dear Candidate, We are looking for a skilled IoT Security Engineer to design and implement security solutions for IoT devices, ensuring secure communication and data protection. Key Responsibilities: Develop security protocols for IoT devices and embedded systems. Implement encryption, authentication, and secure firmware updates for IoT networks. Conduct IoT penetration testing and vulnerability assessments. Monitor and analyze IoT threat intelligence to mitigate risks. Required Skills & Qualifications: Experience with IoT security frameworks (OWASP IoT, NIST IoT Cybersecurity Framework). Knowledge of communication protocols (MQTT, CoAP, Zigbee, LoRaWAN). Hands-on experience in securing edge devices and sensor networks. Soft Skills: Strong problem-solving and analytical skills. Excellent communication skills to work with cross-functional teams. Ability to work independently and as part of a team. Detail-oriented with a focus on delivering high-quality solutions Note: If you are interested, please share your updated resume and suggest the best number & time to connect with you. If your resume is shortlisted, one of the HR from my team will contact you as soon as possible. Srinivasa Reddy Kandi Delivery Manager Integra Technologies

The ideal candidate will possess deep expertise in microcontroller programming, real-time operating systems, and diverse communication protocols, all aimed at bolstering system connectivity and operational efficiency. Key Responsibilities: System Architecture and Embedded Development: Lead the architecture and development of robust embedded systems utilizing microcontrollers like Raspberry Pi Pico and ESP32. Harness expertise in FreeRTOS and Embedded C while exploring innovative programming languages such as Embedded Python to push system capabilities further. Device Integration and Communication Protocols: Design and implement sophisticated communication protocols including USB, RS-232, UART, Wi-Fi, Bluetooth (BLE 5.0). Ensure flawless data transfer and interfacing among integrated systems and hardware devices. IoT Connectivity and Application Integration: Develop comprehensive IoT solutions and craft APIs to enhance connectivity between embedded systems and mobile/web applications. Employ innovative connectivity technologies such as LoRa, Bluetooth (BLE 5.0) for expansive system integration. Power and Data Management: Strategize and refine power management systems and devise advanced battery management techniques. Implement robust data storage solutions to maintain the integrity and security of data across systems. Technical Leadership and Innovation: Lead technical troubleshooting, system testing, and exploration of future technologies. Champion the adoption of next-generation RTOS solutions and pioneering programming languages to maintain technological leadership. Project Management and Collaboration: Work closely with cross-functional teams to achieve project milestones. Manage and lead projects from conception to implementation, aligning with strategic aims and adhering to industry standards. Primary Qualifications: Education: Bachelors or Masters degree in Electronics Engineering, Electrical Engineering, Computer Science, or a related technical field. Experience: At least 12 years of direct experience in embedded systems design and development, with a strong emphasis on IoT and device integration. Technical Proficiency: Ability in microcontroller platforms like Raspberry Pi Pico and ESP32; profound knowledge of FreeRTOS; skilled in programming languages such as Embedded C, and familiarity with Embedded Python. Protocol Expertise: Extensive knowledge of essential communication protocols for IoT and device integration, including USB, RS-232, UART, Wi-Fi, LoRa, Bluetooth (BLE 5.0). Systems Integration: Proven ability to integrate complex hardware systems within a connected environment, improving performance and reliability. Desired Qualifications: Industry-Specific Experience: Hands-on experience with dairy technology devices, such as milk analyzers and weighing machines, understanding their communication and operational specifics. Regulatory Knowledge: Knowledge of industry standards and regulatory requirements pertinent to dairy and precision measurement sectors. Innovation and Research: Keen interest in and ability to embrace and lead the integration of innovative technologies and methodologies in embedded systems. Communication Skills: Exceptional verbal and written communication skills, capable of effectively conveying complex technical information to both technical and non-technical audiences.

Role & responsibilities Key Responsibilities Develop and maintain backend applications using Node.js and TypeScript Build and optimize RESTful APIs and microservices using Express, Fastify, or AdonisJS Design and manage MongoDB databases, ensuring efficiency and scalability Work with Linux and Bash for server management, automation, and deployment tasks Implement LLM LoRA fine-tuning and optimize LLM models using Hugging Face Transformer Trainer or other advanced techniques (Preferred) Set up and manage CI/CD pipelines , ensuring smooth deployment and integration processes Deploy and optimize cloud infrastructure using AWS Beanstalk or Kubernetes-based infra Would be a plus. Work on AI-driven coding workflows , integrating Vibe Coding methodologies Utilize Generative AI agents like Cursor or Cline to enhance development efficiency Required Skills and Experience 5+ years of experience in backend development with Node.js and TypeScript Proficiency in Express, Fastify, or AdonisJS for building scalable applications Strong expertise in MongoDB , including schema design, indexing, and optimization Hands-on experience with Linux and Bash scripting for system automation Familiarity with Hugging Face Transformer Trainer or LoRA fine-tuning for LLMs (Preferred) Experience in setting up CI/CD pipelines using GitHub Actions, Jenkins, or similar tools Knowledge of AWS Beanstalk, Kubernetes (K8s), or cloud infrastructure deployment Exposure to Vibe Coding methodologies and AI-assisted development tools like Cursor or Cline (Huge Plus) Strong debugging and troubleshooting skills for backend applications Preferred Qualifications Experience with GraphQL or tRPC for efficient API communication Background in distributed systems and microservices architecture Familiarity with serverless computing and cloud-native technologies

Role & responsibilities Conduct security assessments and risk analysis of embedded medical devices Develop and implement security protocols and solutions for medical devices Design and execute penetration testing and vulnerability assessments Research and stay updated on emerging threats, vulnerabilities, and security trends in IoT and embedded systems. Collaborate with cross-functional teams to integrate security measures into the development lifecycle of products. Provide technical guidance and support to internal teams on security best practices. Participate in the design and architecture of secure IoT and embedded systems. Preferred candidate profile Mandatory Skills: Proven experience (5 years) in IoT and embedded systems security. Strong knowledge of IoT protocols (e.g., UART, I2C, JTAG, MQTT, CoAP, HTTP) and embedded system architecture Experience with reverse engineering ARM/MIPS/x86 code architecture Hands on with hardware attacks such as PCB reversing, Component identification,Side channel attacks,memory extraction methods Knowledge of radio frequency (RF) protocols and related security implications such as BLE, WIFI, LoRa,DSP, SDR, etc Understanding of industrial IoT (IIoT) security considerations. Experience with various hardware security assessment tools/frameworks. Familiarity with hardware security concepts such as secure boot, encryption, and secure firmware updates. Proficiency in programming languages commonly used in embedded systems (C/C++, Python). Proactive, problem-solver and the ability to work independently and within a team Good to Have : Understanding of cryptographic algorithms and protocols Knowledge of exploit development techniques, buffer overflows, and other memory corruption vulnerabilities applicable to embedded systems Knowledge of secure coding practices and principles specific to embedded systems, including memory management and input validation Familiarity with regulatory compliance and standards in IoT security Any certification in IoT security, Embedded device security or similar, is a plus. Perks and benefits

Job Description Role & Responsibilities: Develop and deploy Generative AI solutions using LLMs and related technologies. Fine-tune large language models (LLM fine-tuning) to improve performance. Work on Retrieval-Augmented Generation (RAG) methodologies to optimize AI outputs. Implement Prompt Engineering techniques for effective model interaction. Utilize Python, TensorFlow, and PyTorch for AI model development and optimization. Work with cloud platforms like Azure, AWS, or GCP to deploy and scale AI models. Collaborate with cross-functional teams to integrate AI solutions into business applications. Maintain AI/ML pipelines and workflows using LLMOps best practices. Preferred Candidate Profile: 5 to 8 years of experience in AI, ML, or Data Science roles. 2 to 3 years of experience specifically in GenAI solution development, LLM fine-tuning, RAG, or LLMOps. Strong background in Natural Language Processing (NLP) and Transformer models. Hands-on experience with cloud-based AI solutions (Azure, AWS, GCP). Excellent problem-solving skills and ability to work in a fast-paced environment. Perks and Benefits: Competitive salary and performance-based incentives. Work with cutting-edge AI technologies and industry leaders. Opportunities for career growth and learning. Health insurance and other standard benefits.