MLOps Senior Engineer – Vector/LLDS Database & AI Platform Focus(Only W2 Candidate)

Ampstek; Austin (TX); On-site; USD 100,000 - 150,000; Full time

Job summary

Ampstek is seeking an experienced MLOps Senior Engineer to focus on Vector/LLDS databases and the AI platform. You will design and optimize production AI pipelines, manage embeddings, and ensure scalable deployment.

The role requires strong Linux, Python automation, and experience with CI/CD, Docker, Kubernetes, and observability tools. This is a contract W2 position in Austin, TX, with responsibilities across data ingestion, model inference, and disaster recovery.

Qualifications

• Hands-on experience with vector databases and similarity search.
• Strong Linux CLI, shell scripting, and debugging skills.
• Python automation for AI models, data pipelines, and OpenAI integrations.
• Familiarity with Hadoop-based platforms (MapR, Hortonworks).
• CI/CD and containerization with Docker/Kubernetes.

Responsibilities

• Support predictive AI workloads in production and monitor data ingestion, model inference, and deployment layers.
• Define and implement observability strategies using Splunk, Grafana, and ELK stack.
• Maintain CI/CD pipelines and containerized deployments; provide on-call support for GenAI pipelines.

Skills

Vector databases

Linux systems

Python programming

Big data technologies

CI/CD pipelines

Docker

Kubernetes

Observability tooling

Tools

Docker

Kubernetes

Splunk

Grafana

ELK stack

OpenTelemetry

Job description

MLOps Senior Engineer – Vector/LLDS Database & AI Platform Focus(Only W2 Candidate)

MLOps Senior Engineer – Vector/LLDS Database & AI Platform Focus(Only W2 Candidate)

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Duration: W2 (Contract )Candidate Only

Job Description::

Experience – 10 +

Core Technical Skills

- Vector Databases: Hands-on experience with Elasticsearch or similar; understanding of similarity search, indexing strategies, and embedding management.

- Linux Systems: Strong command-line skills; shell scripting; system-level monitoring and debugging.

- Python Programming: Proficient in automation scripting; experience in building AI models, data pipelines, and OpenAI integrations.

- Big Data Technologies: Familiarity with Hadoop-based platforms like MapR and Hortonworks.

AI Platform & Production Support

- Experience supporting predictive AI workloads in production.

- Troubleshooting across data ingestion, model inference, and deployment layers.

- Familiarity with CI/CD pipelines and containerization (Docker, Kubernetes).

- On-call support for GenAI and predictive pipelines (1 week every 6–8 weeks).

- Understanding of enterprise disaster recovery (DR) solutions including backup and restore.

Observability & Monitoring

- Ability to define and implement observability strategies for AI systems.

- Experience with tools such as Splunk, Grafana, ELK stack, OpenTelemetry.

- Proactive monitoring of model failures, latency, and system health.

Bonus Qualifications

- Multi-cloud Experience: Exposure to GCP and Azure environments.

- Data Science Lifecycle: Involvement in full-cycle projects including problem definition, data exploration, modeling, evaluation, training, scoring, and operationalization.

- MLOps Principles: Understanding of model lifecycle management and collaboration with data scientists to deploy solutions

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Contract

Job function

• Industries

  IT Services and IT Consulting

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