RE: Job Opportunity : Senior AI/ML Engineer - Hanover, MD(Hybrid) - 6 months + (Potential for Extension)

[Venu Goud]

Job Opportunity: Senior AI/ML Engineer

Location: Hanover, MD(Hybrid)                                                                                                                                                                                                                                 

Duration:  6 months + (Potential for Extension)

Send me the resumes to Ve...@techrakers.com

Only H1B'S. Locals required

                                                                                                                                                                                                                                           

Job Description:

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—GCP (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.

• Experience working with Snowflake—SQL, stored procedures, and core objects (Snowpipe, Streams, Tasks); exposure to Cortex AI is a plus.

• Working knowledge of a major cloud platform—GCP (Vertex AI, Cloud Run, Cloud Functions) preferred, given the current stack.

• Experience building and maintaining data pipelines and orchestration.

• Proficiency with version control (Git), RESTful API design, and containerization (Docker).

• Experience with observability and monitoring tools (Grafana, Prometheus, Splunk, Tableau, or equivalent).

 

Nice to Haves:

• Experience taking enterprise AI agents to production and operating them with observability and cost controls (Snowflake, GCP, and Salesforce).

• Hands-on experience with Snowflake Cortex AI (LLM functions, fine-tuning) or other LLM/GenAI productionization.

• Exposure to search/matching technologies such as Elasticsearch, or to NLP and recommendation systems.

• Familiarity with data governance, responsible AI (bias, safety, ethics), and regulatory/ML audit requirements.

• Experience with AI coding assistants and agentic development workflows (e.g., Claude Code, GitHub Copilot, Cursor).

• Snowflake or cloud (GCP/Azure/AWS) certification.

 

Education Required:

• Bachelor's or master's degree in computer science, Data Science, Engineering, or a related field, or equivalent practical experience.