My name is Omkar Nath Sharma and I represent Synchrony Systems Inc. We are currently supporting an implementation partner on a full-time opportunity. Based on your background your experience may align well with this role.
Position Details:
Role:
AI Ops Engineer
Locations:
Remote
Employment Type:
Full-Time (W2 only)
Work Model:
Remote
Compensation: Base salary range of
$100000 $120000 per year plus benefits
Experience Range
Min 8 Years to Max 22 Years
Work Authorization
Who can work on a full-time W2 basis without sponsorship
Note:
This role is not open for C2C/C2H/1099 or any contract arrangements
This opportunity is available for candidates who can work on a full-time W2 basis without sponsorship.
Job Description
Must Have Technical/Functional Skills:
We are seeking a AI OPS Engineer with Builds trains and tunes machine learning models. Translates data science experiments into scalable production-ready ML solutions.
Roles & Responsibilities:
Translate data science prototypes into production-grade ML services and pipelines.
Build training and inference code with reproducibility versioning and automated testing.
Implement scalable model serving (online/offline) batching and latency/throughput optimization.
Integrate model lifecycle tooling (tracking registry deployment automation monitoring).
Collaborate with Data Engineering on feature pipelines and data contracts.
Own production health: drift detection performance regression rollback strategies and incident response.
Required Qualifications
5 years software engineering with 2 years shipping ML models to production.
Strong Python skills and experience with ML frameworks (TensorFlow/PyTorch).
Experience with containers and orchestration (Docker/Kubernetes) and API development.
Understanding of ML system design (data leakage training-serving skew drift).
CI/CD and DevOps practices applied to ML workloads (MLOps).
Experience with CI/CD and DevOps practices applied to ML (MLOps)
Dear Consultant I hope you are doing well. My name is Omkar Nath Sharma and I represent Synchrony Systems Inc. We are currently supporting an implementation partner on a full-time opportunity. Based on your background your experience may align well with this role. Position Details: Role...
Dear Consultant
I hope you are doing well.
My name is Omkar Nath Sharma and I represent Synchrony Systems Inc. We are currently supporting an implementation partner on a full-time opportunity. Based on your background your experience may align well with this role.
Position Details:
Role:
AI Ops Engineer
Locations:
Remote
Employment Type:
Full-Time (W2 only)
Work Model:
Remote
Compensation: Base salary range of
$100000 $120000 per year plus benefits
Experience Range
Min 8 Years to Max 22 Years
Work Authorization
Who can work on a full-time W2 basis without sponsorship
Note:
This role is not open for C2C/C2H/1099 or any contract arrangements
This opportunity is available for candidates who can work on a full-time W2 basis without sponsorship.
Job Description
Must Have Technical/Functional Skills:
We are seeking a AI OPS Engineer with Builds trains and tunes machine learning models. Translates data science experiments into scalable production-ready ML solutions.
Roles & Responsibilities:
Translate data science prototypes into production-grade ML services and pipelines.
Build training and inference code with reproducibility versioning and automated testing.
Implement scalable model serving (online/offline) batching and latency/throughput optimization.
Integrate model lifecycle tooling (tracking registry deployment automation monitoring).
Collaborate with Data Engineering on feature pipelines and data contracts.
Own production health: drift detection performance regression rollback strategies and incident response.
Required Qualifications
5 years software engineering with 2 years shipping ML models to production.
Strong Python skills and experience with ML frameworks (TensorFlow/PyTorch).
Experience with containers and orchestration (Docker/Kubernetes) and API development.
Understanding of ML system design (data leakage training-serving skew drift).
CI/CD and DevOps practices applied to ML workloads (MLOps).
Experience with CI/CD and DevOps practices applied to ML (MLOps)