AI/ML Engineer

🔥 3 minutes ago

⚔️ Virginia – Remote

⚔️ Virginia – Remote

💵 $103.2k - $196.4k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 0%

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Accenture Federal Services

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 2017

💼 Consulting

🎖️ Defense

📦 Logistics

Consulting • Defense • Logistics

Accenture Federal Services is a division of Accenture that focuses on delivering technology and consulting services to the U. S. federal government. With capabilities in cloud, cybersecurity, data and artificial intelligence, digital engineering, and emerging technologies, Accenture Federal Services supports federal agencies in achieving mission-critical outcomes through innovation and technological advancement. The company emphasizes building secure, scalable solutions, enhancing decision-making with data-driven insights, and transforming digital infrastructures to meet complex governmental needs. By leveraging advanced R&D and human-centered design, they aim to improve the performance and resilience of government operations.

📋 Description

• Partner with stakeholders to identify and refine AI/ML use cases and translate business needs into technical solutions • Design, build, fine-tune, and evaluate ML and GenAI models, including LLMs, RAG, embeddings, and deep learning, using Vertex AI, Gemini, and open-source tools • Develop end-to-end ML pipelines covering data ingestion, feature engineering, orchestration, and CI/CD for models and prompts • Deploy scalable models and agents; manage monitoring, drift detection, and production troubleshooting • Collaborate with data engineering teams on high-quality data architecture using BigQuery, Dataflow, Pub/Sub, and Feature Store • Implement Responsible AI, security, governance, and compliance best practices including IAM, encryption, and auditing • Work cross-functionally with product owners, platform teams, DevOps/SRE, and junior engineers to deliver reliable AI solutions • Perform experimentation, prototyping, exploratory data analysis, hyperparameter tuning, and documentation of pipelines and workflows

🎯 Requirements

• US Citizen (Public Trust Eligible) • 3–6+ years in machine learning engineering, data science, or AI development • 3+ years of experience leading technical teams to achieve objectives and outcomes • Experience developing and implementing technical standards, systems, and processes for cloud and on-prem environments • Experience recommending technology strategies and decisions with a high level of expertise and knowledge • Experience providing technical direction and support to ensure compliance with standards and guidelines • Google Storage experience, including access control, versioning, encryption, lifecycle management, logs, backups, static files, ML workflows, Storage Transfer Service, Cloud Storage, Cloud Storage for Firebase, Filestore, Google Workspace Essentials, Local SSD, and Persistent Disk • Python and SQL • TensorFlow, PyTorch, scikit-learn, Transformers, LLM fine-tuning, and RAG architectures • Vertex AI, Gemini APIs, BigQuery, Cloud Storage, KMS, and IAM • Vertex AI Pipelines, Dataflow, Pub/Sub, and Feature Store • Experience with Vertex AI Search, Agents, RAG solutions, or vector databases such as Vertex Vector Search, Pinecone, or Milvus • Experience deploying AI workloads on Kubernetes or microservices architectures • Google Cloud Professional certification (ML Engineer, Data Engineer, or Architect) • Hands-on experience with Vertex AI, Gemini APIs, or other cloud-based AI/ML platforms • Strong Python development skills and familiarity with ML frameworks • Strong understanding of LLMs, embeddings, vector search, and generative AI techniques • Must be authorized to work in the United States without current or future visa sponsorship • Preferred: knowledge of Responsible AI, bias mitigation, and model interpretability • Preferred: familiarity with GCP operational tools including IAM, KMS, Logging/Monitoring, VPC, and Cloud Storage • Preferred: exposure to AWS/Azure equivalents or third-party security, observability, and DevOps tools • Preferred: Master’s degree and prior federal or regulated-industry experience

🏖️ Benefits

• Collaborative and caring community • Hands-on experience • Certifications • Industry training • Wide variety of benefits • Reasonable accommodations for disabilities or religious observances during recruiting and employment processes