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fractal

Senior AI Engineer_ MLOPs_ 5 to 10yrs

Bengaluru · Senior

Older listing - lower visibility likelyVerified listingPosted 32d ago

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Skills required

17 listed
CI/CDMachine LearningBusiness DevelopmentSystems IntegrationC# (Programming Language)MLOps (Machine Learning Operations)MLflowKubeflow+9 more
CI/CDMachine LearningBusiness DevelopmentSystems IntegrationC# (Programming Language)

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Job description

It's fun to work in a company where people truly BELIEVE in what they are doing!

We're committed to bringing passion and customer focus to the business.

JOB LOCATION:

Bangalore, Mumbai, Pune, Gurgaon, Chennai, Hyderabad, Coimbatore, Noida

JOB DESCRIPTION:

Building the machine learning production System(or MLOps) is the biggest challenge most large companies currently have in making the transition to becoming an AI-driven organization. This position is an opportunity for an experienced, server-side developer to build expertise in this exciting new frontier. You will be part of a team deploying state-of-the-art AI solutions for Fractal clients.
 

RESPONSIBILITIES:

As MLOps Engineer, you will work collaboratively with Data Scientists and Data engineers to deploy and operate advanced analytics machine learning models. You’ll help automate and streamline Model development and Model operations. You’ll build and maintain tools for deployment, monitoring, and operations. You’ll also troubleshoot and resolve issues in development, testing, and production environments.

• Enable Model tracking, model experimentation, Model automation • Develop scalable ML pipelines

• Develop MLOps components in Machine learning development life cycle using Model Repository (either of): MLFlow, Kubeflow Model Registry

Machine Learning Services (either of): Kubeflow, DataRobot, HopsWorks, Dataiku or any relevant ML E2E PaaS/SaaS

• Work across all phases of Model development life cycle to build MLOPS components

• Build the knowledge base required to deliver increasingly complex MLOPS projects on the Cloud(AWS, Azure, GCP)/On Prem • Be an integral part of client business development and delivery engagements across multiple domains.

QUALIFICATIONS: REQUIRED QUALIFICATIONS:

• 5-10 years experience building production-quality software

• Strong experience in System Integration, Application Development or DataWarehouse projects across technologies used in the enterprise space

• Basic Knowledge of MLOps, machine learning and docker

• Object-oriented languages (e.g. Python, PySpark, Java, C#, C++ )

• Experience developing CI/CD components for production ready ML pipeline.

• Database programming using any flavors of SQL

• Knowledge of Git for Source code management

• Ability to collaborate effectively with highly technical resources in a fast-paced environment

• Ability to solve complex challenges/problems and rapidly deliver innovative solutions

• Team handling, problem solving, project management and communication skills & creative thinking

• Foundational Knowledge of Cloud Computing either one AWS, Azure or GCP

• Hunger and passion for learning new skills

EDUCATION:

B.E/B.Tech/M.Tech in Computer Science or related technical degree OR Equivalent.

If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!

Not the right fit?  Let us know you're interested in a future opportunity by clicking Introduce Yourself in the top-right corner of the page or create an account to set up email alerts as new job postings become available that meet your interest!

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Applicants who checked fit first are 3.1× more likely to hear back

Your match scoreFree · sign in
86Overall
64Skills
97Experience

Your score for this role already exists

ASAI compared this JD against 41 signals - skills, seniority, domain, stack overlap etc. Add a resume and it unlocks in about 30 seconds.

Always free · no credit card · 1 tap with Google

Free · no signup

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Why people use ASAI

Someone shared one job with you. ASAI keeps finding the rest.

  • Scored, not searched. Every role ranked against your actual profile.

  • Alerts as often as hourly. Reach new roles while the pile is still small.

  • Skill gaps, spelled out. See exactly which requirements you don't meet yet.

  • Verified jobs, only. Say no to ghost jobs. Your time deserves respect.

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