Hyderabad Job Vacancies at Capgemini Digital Drive 2025

Hyderabad Job Vacancies  at Capgemini Know-how Companies India Restricted is actively hiring skilled MLOps Engineers by way of its Digital Drive initiative. With a global presence in over 40 worldwide places and a sturdy legacy of providing revolutionary consulting, digital, and outsourcing choices, Capgemini gives a dynamic platform for profession development. As an MLOps Engineer, you’ll be a part of a high-performing workforce that builds, deploys, and manages machine studying to get to know fashions at scale. This operate calls for a mix of improvement, operations, and knowledge technological know-how. Be a part of Capgemini to make a contribution to superior AI solutions, work on thrilling digital transformation duties, and be a part of a world chief in expertise innovation.

Capgemini Digital Drive Overview

• Firm:-Capgemini
• Wage:- Not Disclosed
• Qualification:– UG, PG
• Skilled:- 0 – 1
• Work Mode:- WFO/WFH
• Job Kind:- Full Time

Hyderabad Job Vacancies

Capgemini is imparting thrilling process vacancies in Hyderabad for people attempting to develop their careers within the IT and digital companies sector. With roles available all through domains, inclusive of software program improvement, MLOps engineering, cloud options, and knowledge analytics, Capgemini gives a dynamic work setting that encourages innovation and studying. The organisation seeks skilled specialists and glowing graduates eager to make a contribution to high-impact tasks for worldwide purchasers. Working at Capgemini Hyderabad, technique am part of a worldwide period chief with a sturdy dedication to worker improvement, range, and collaboration. That is your danger to enroll in a gaggle shaping the way forward for digital transformation.

In regards to the Function

Capgemini is hiring MLOps Engineers to useful resource the advance and deployment of machine studying fashions into manufacturing environments. This operate consists of shut collaboration with knowledge scientists, builders, and DevOps organizations to assemble scalable and dependable ML infrastructure. As an MLOps Engineer, you’ll format automation pipelines, show model general efficiency, and guarantee seamless integration of AI solutions with enterprise packages. Chances are you’ll be a part of an extreme-acting worldwide workforce, utilizing the present cloud technology, CI/CD practices, and DevOps instruments. This can be a good risk for folks captivated with AI, info engineering, and operationalizing machine studying to realize information of solutions. Hyderabad Job Vacancies

Obligations Hyderabad Job Vacancies

As an MLOps Engineer at Capgemini, your heart responsibility is to bridge the area between system studying enchancment and manufacturing deployment. You’ll broaden, arrange, and maintain a scalable system finding out fashions the utilization of cutting-edge MLOps frameworks and instruments. You’ll be accountable for designing and automating give-up-to-prevent information pipelines, guaranteeing seamless integration between knowledge ingestion, preprocessing, mannequin coaching, and deployment. Hyderabad Job Vacancies

Key duties embody establishing CI/CD pipelines for ML workflows, configuring cloud-based ML environments (AWS, Azure, GCP), and monitoring mannequin common efficiency via using logging and alert buildings. You’ll additionally work on mannequin manipulation of fashions and information, allow model retraining, and implement mannequin governance practices. Moreover, you’ll collaborate with move-sensible teams to make sure a stable, scalable, and optimized model execution. Hyderabad Job Vacancies

Troubleshooting, maintaining infrastructure reliability, and implementing glorious practices for DevOps contained in the ML space could be important. Sturdy information of containerization (Docker, Kubernetes), scripting languages (Python, Bash), and ML system (MLflow, TensorFlow, PyTorch) is anticipated. The attribute moreover calls for non-prevent studying to adapt to evolving system and methodologies inside the MLOps panorama.

Who Can Apply?

Candidates with a bachelor’s or maintain shut’s diploma in Laptop Science, Knowledge Science, Engineering, or associated fields are endorsed to make use of. Recent graduates with related tutorial initiatives in machine studying, AI, or DevOps are welcome. Professionals with as much as three years of expertise in MLOps, DevOps, or ML engineering are ideally suited.

Candidates must have a superb understanding of system mastering algorithms and sensible experience with ML libraries like Scikit-study, TensorFlow, or PyTorch. Expertise in cloud system (AWS, Azure, or GCP) is a bonus. Impact in python and scripting, with the first understanding of mannequin manipulation (gIT), container (doorways), and orchestration (Kuberanets), is useful. Sturdy analytical and problem-solving skills, curiosity to check, and associates are the flexibility of artwork work in tight groups. Information of CI/CD pipelines, mannequin deployment, monitoring gear, and ML lifecycle administration is a plus.

Capgemini values selection and encourages candidates from all backgrounds, together with girls returnees, in a unique way-abled people, and profession switchers with relevant tech certifications. Ardour for innovation, notable dialog skills, and a powerful work ethic will aid you stand out.

Why Apply?

Becoming a member of Capgemini as an MLOps Engineer technique being part of a worldwide tech chief with a powerful status for digital innovation and employee improvement. You’ll be engaged on thrilling AI/ML tasks with international purchasers, gaining hands-on get pleasure from in cloud computing, DevOps, and gadget mastering.

Capgemini gives attached mastering paths, profession mobility, and a collaborative work setting that helps continuous increase. With its inclusive lifestyle and versatile work choices, it is a nice risk for aspiring tech specialists looking for to form the way forward for AI-pushed options. Apply now to launch a worthwhile profession with limitless potentialities at Capgemini!

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