Senior AI/ML Engineer

Hybrid in Elkridge, MD, US • Posted 1 day ago • Updated 1 day ago
Contract Independent
Contract W2
12 Months
No Travel Required
Hybrid
Depends on Experience
Fitment

Dice Job Match Score™

⭐ Evaluating experience...

Job Details

Skills

  • API
  • Artificial Intelligence
  • Auditing
  • Cloud Computing
  • Collaboration
  • Continuous Delivery
  • Continuous Integration
  • Dashboard
  • Data Engineering
  • Database
  • Deep Learning
  • Documentation
  • Generative Artificial Intelligence (AI)
  • Good Clinical Practice
  • Google Cloud Platform
  • Machine Learning (ML)
  • Machine Learning Operations (ML Ops)
  • Management
  • NumPy
  • Orchestration
  • Pandas
  • Production Support
  • Prompt Engineering
  • PyTorch
  • Python
  • Real-time
  • SQL
  • Scratch
  • Stored Procedures
  • Streaming
  • TensorFlow
  • Use Cases
  • Vertex
  • Workflow
  • scikit-learn

Summary

Hi,
 
We do have an urgent requirement for the below position with our direct client, Please submit Resume, Rate and Contact details.
Position: Senior AI/ML Engineer
Location: Hanover MD (Hybrid)
Duration: Long Term

Top Skills:

Senior AI/ML Engineer with 5-8 years of experience with:
  • MLOps - CI/CD pipelines, model/agent versioning, automated retraining, and production monitoring
  • Strong programming skills in Python
  • Hands-on experience building, deploying, and maintaining AI agents/agentic workflows using modern frameworks LLMs and GenAI patterns
  • Snowflake - SQL, stored procedures, and core objects (Snowpipe, Streams, Tasks); exposure to Cortex AI is a plus
  • A major cloud platform - Google Cloud Platform (Vertex AI, Cloud Run, Cloud Functions) preferred, given the current stack
Key Responsibilities:
  • Design, develop, and evaluate machine learning and deep learning models in Python, taking them from prototype to production-ready APIs and services.
  • Build AI agents and agentic workflows from scratch for enterprise use cases, using modern agentic frameworks and LLM orchestration patterns such as RAG, tool use, multi-agent coordination, and structured outputs.
  • Own deployed agents end to end: refine prompts, tune retrieval and tools, manage versioning, and continuously improve accuracy, latency, safety, and cost over time.
  • Perform data preprocessing, feature engineering, and pipeline development across large datasets to support model and agent workloads.
  • Implement model/agent registries, versioning, and automated retraining cycles (e.g., scheduled retraining) with reproducible, well-documented pipelines.
  • Instrument metrics, alerting, and dashboards for model performance, data drift, agent quality, token/cost usage,
  • and pipeline failures (e.g., Snowsight, audit tables, LLM tracing, real-time API metrics).
  • Contribute reusable MLOps frameworks, templates, and documentation that other DSV engineers can adopt across projects.
  • Build validation, error logging, and audit capabilities into pipelines; apply responsible AI, PII handling, and content moderation practices, and support governance and regulatory audit requirements.
  • Collaborate with data scientists, platform/infrastructure teams, and product owners to translate requirements into reliable production systems.
  • Provide production support for live models, agents, and pipelines; triage failures and drive continuous reliability and cost improvements.
Required Skills & Qualifications:
  • 5-8 years of professional experience in AI/ML engineering, data engineering, or a closely related role.
  • Strong programming skills in Python (e.g., NumPy, pandas, scikit-learn, and a deep learning framework such as TensorFlow or PyTorch) and proficiency in SQL.
  • Hands-on experience building, deploying, and maintaining AI agents/agentic workflows using modern frameworks.
  • Practical experience with LLMs and GenAI patterns—prompt engineering, retrieval-augmented generation (RAG), tool/function calling, and structured outputs.
  • Demonstrated MLOps experience—CI/CD pipelines, model/agent versioning, automated retraining, and production monitoring.
  • Experience deploying and operating models in production (as APIs, batch jobs, or in-database functions), not just model development.
 
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 90943978
  • Position Id: 9017866
  • Posted 1 day ago
Contact the job poster
Vamsi Krishna

Vamsi Krishna

Senior Talent Acquisition Specialist @ SSTech LLC
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