AI / ML Engineer

Job Title: AI / ML Engineer Job Type: Full-Time Location: Remote (U.S. based) Clearance Requirement: U.S. Citizenship and Green card holder with the ability to obtain a clearance Must be a US Citizen OR GC Holder Only JOB DESCRIPTION 1. Position Overview Avilamb Inc. is seeking an AI / ML Engineer to design, build, deploy, and operate production AI/ML and generative AI solutions on Google Cloud Platform (GCP). The role focuses on Vertex AI, Gemini, model development, MLOps, data pipelines, secure cloud integration, and responsible AI practices. 2. Key Responsibilities Partner with stakeholders to identify and refine AI/ML use cases and translate business requirements into technical designs.Design and develop supervised, unsupervised, deep learning, and generative AI/ML models.Build, fine-tune, and evaluate LLM solutions using Gemini APIs, Vertex AI Model Garden, and open-source models.Implement RAG patterns, embeddings, vector stores, and agent-based workflows.Build end-to-end ML pipelines using Vertex AI Pipelines, BigQuery, and managed datasets.Implement CI/CD, automated testing, and versioning for models, prompts, and datasets.Deploy and monitor models in production, including performance, latency, drift, errors, fairness, bias, and robustness.Collaborate on scalable data ingestion, transformation, and storage using BigQuery, Dataflow, Pub/Sub, and Vertex Feature Store.Apply IAM, KMS, encryption, audit logging, governance, and responsible AI practices.Write production-grade Python for training, inference, orchestration, and troubleshooting. 3. Required Qualifications Minimum 3 years of experience leading technical teams to achieve objectives and outcomes, including technical standards/processes, technology recommendations, and technical direction.Bachelor’s degree in Computer Science, Data Science, Engineering, or related field, or equivalent practical experience.3–6+ years of machine learning engineering, data science, or AI development experience.Hands-on experience with Vertex AI, Gemini APIs, or comparable cloud AI/ML platforms.Strong Python skills and experience with TensorFlow, PyTorch, or scikit-learn.Experience deploying and monitoring ML models in production.SQL and cloud data warehouse experience, preferably BigQuery.Experience with CI/CD, containers, automated deployments, LLMs, embeddings, vector search, and generative AI. 4. Preferred Qualifications Master’s degree in a relevant field.Federal Government experience.Experience with regulated environments such as FedRAMP, HIPAA, NIST 800-53, or CIS benchmarks.Vertex AI Search, Agents, RAG solutions, and vector databases.Dataflow, Pub/Sub, Kubernetes, microservices, responsible AI, and model interpretability.Google Cloud Professional certification such as Machine Learning Engineer, Data Engineer, or Cloud Architect. 5. Technical Environment GCP: Vertex AI, Gemini APIs, BigQuery, Cloud Storage, IAM, KMS, Vertex AI Pipelines, Dataflow, Pub/Sub, Feature Store.ML/GenAI: TensorFlow, PyTorch, scikit-learn, Transformers, LLM fine-tuning, RAG.MLOps/DevOps: Git, GitHub/GitLab, CI/CD, Docker, Kubernetes, experiment tracking, model registries.Observability/Security tools may include Cloud Logging/Monitoring, Splunk, Dynatrace, Tenable Nessus, CrowdStrike, Armis, Centrify, BigFix, NetSkope, ServiceNow, Jira, Turbot, Apptio, and Cloudability.