AI / ML Engineer
New
A
Accenture Federal ServicesAI and machine learning
Workplace Type: RemoteFull-TimeMiddle
Salary103,200 - 196,400 USD per year
Apply NowOpens the employer's application page
Job Details
- Experience
- 3–6+ years in machine learning engineering, data science, or AI development; 3+ years of experience in leading technical teams
- Required Skills
- PythonSQLPyTorchTensorflowscikit-learn
Requirements
- Bring 3–6+ years of experience in machine learning engineering, data science, or AI development.
- Have 3+ years of experience leading technical teams to achieve objectives and outcomes.
- Have experience developing and implementing technical standards, systems, and processes for cloud and on-prem environments.
- Be able to recommend technology strategies and decisions and provide technical direction and support for compliance with standards and guidelines.
- Have hands-on experience with Vertex AI, Gemini APIs, or other cloud-based AI/ML platforms.
- Have strong Python development skills and familiarity with TensorFlow, PyTorch, and scikit-learn.
- Understand LLMs, embeddings, vector search, and generative AI techniques.
- Have experience with Vertex AI Search, agents, RAG solutions, or vector databases such as Vertex Vector Search, Pinecone, or Milvus.
- Have experience deploying AI workloads on Kubernetes or microservices architectures.
- Have knowledge of Vertex AI Pipelines, Dataflow, Pub/Sub, Feature Store, BigQuery, Cloud Storage, KMS, and IAM.
- Google Cloud Professional certification in ML Engineering, Data Engineering, or Architecture is listed.
- Preferred: a master’s degree; federal or regulated-industry experience; Responsible AI, bias mitigation, and model interpretability; GCP operational tools; or exposure to AWS/Azure equivalents and third-party security, observability, or DevOps tools.
Responsibilities
- 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 using Vertex AI, Gemini, and open-source tools.
- Develop end-to-end ML pipelines for data ingestion, feature engineering, orchestration, and CI/CD for models and prompts.
- Deploy scalable models and agents, and manage monitoring, drift detection, and production troubleshooting.
- Collaborate with data engineering teams on data architecture using BigQuery, Dataflow, Pub/Sub, and Feature Store.
- Implement Responsible AI, security, governance, and compliance practices, including IAM, encryption, and auditing.
- Work with product owners, platform teams, DevOps/SRE, and junior engineers to deliver AI solutions.
- Conduct experimentation, prototyping, EDA, and hyperparameter tuning, and document pipelines and workflows.
View Full Description & ApplyYou'll be redirected to the employer's site
