Design and implement end-to-end ML architectures and scalable Java backend systems, and create cross-platform solution architectures. Lead model lifecycle, MLOps standards, cloud-native deployments, microservices design, integrations, CI/CD, and stakeholder alignment across product, data engineering, and infrastructure teams.
This is a remote position.
1. Job Title: AI/ML Architect
Key Responsibilities: Design and review machine learning architecture pipelines end-to-end. Architect scalable models using tools like TensorFlow, PyTorch, Scikit-learn. Drive data strategy, feature stores, model lifecycle (training, deployment, monitoring). Collaborate with data engineering and product teams to align technical goals. Define standards for MLOps, model governance, and responsible AI.
Must-Have Skills: 8+ years in ML/DL, data science, or AI-related roles. Expertise in Python, ML frameworks, distributed computing (Spark, Dask). Cloud-native ML deployment on AWS SageMaker, Azure ML, GCP Vertex AI. Knowledge of Kubeflow, MLFlow, Airflow, Docker/K8s for ML pipelines. Strong grasp of ML lifecycle management, monitoring, and retraining.
2. Job Title: Java Architect
Key Responsibilities: Own the technical design for backend systems built on Java / Spring Boot. Create solution blueprints, architecture documents, and design patterns. Guide teams on microservices, containerization, API design, and DevOps. Conduct code reviews, architecture assessments, and risk mitigation. Collaborate with product and infrastructure teams for seamless delivery.
Must-Have Skills: Proficiency in Java 11+/Spring Boot, RESTful APIs, ORM frameworks. Experience with Kubernetes, Docker, messaging systems (Kafka, RabbitMQ). Strong grasp of cloud-native development (AWS, Azure, GCP). In-depth understanding of microservices, DDD, clean architecture. Performance tuning, scalability, and reliability design.
3. Job Title: Solution Architect
Key Responsibilities: Analyze requirements and design technical solutions across platforms. Create architecture roadmaps for applications, integrations, and cloud infrastructure. Lead POCs, architecture evaluations, and tech selection. Align solutions with enterprise architecture standards and security best practices. Act as a technical bridge between stakeholders, developers, and leadership.
Must-Have Skills: Strong experience in application architecture, APIs, and system integration. Familiarity with cloud platforms (Azure, AWS, GCP). Solid understanding of data architecture, DevOps practices, CI/CD pipelines. Experience with design patterns, scalability, and resilience planning. Great communication, documentation, and stakeholder management skills.
Similar Jobs
Enterprise Web • HR Tech • Information Technology • Software • Cybersecurity
Sell Immersive's cyber resilience SaaS to large enterprise clients in the US East region, acquire net-new flagship accounts, retain and grow account value, coordinate with marketing, pre-sales, channel partners and customer success, and represent the company at industry events.
Artificial Intelligence • Cloud • Sales • Security • Software • Cybersecurity • Data Privacy
Lead end-to-end execution of a 12+ initiative product security program, managing cross-team dependencies, vendor procurement, BAU security operations, and executive reporting. Maintain roadmap and tracking in Jira/Confluence, drive procurement/POCs, produce executive-ready metrics, and establish program cadence to ensure timely remediation and predictable delivery.
Top Skills:
Ai And Machine LearningCi/CdCloud-Native SecurityConfluenceDevsecopsIdentity And Access Management (Iam)JIRAScmVulnerability Management
Artificial Intelligence • Machine Learning • Natural Language Processing • Software • Conversational AI
Build and scale Deepgram's federal partner network by owning strategy and execution for SI/prime and hyperscaler alliances. Drive sell-to/sell-through/sell-with motions, create joint solutions, enable partners at scale, instrument partner-sourced/influenced pipeline, and deploy AI-native automations to operate at scale. Represent Deepgram externally and coordinate cross-functionally to accelerate partner-driven revenue.
Top Skills:
Agentic AiAgentsAws Connect GovcloudCio-Sp3CRMDeepgramDod Impact LevelFedrampGenesys GovernmentGovcloudGsa MasGwacsLlmsNasa SewpNiceRetrieval Augmented Generation (Rag)Sam.GovServicenow FederalSlackSpeech-To-Text (Stt)Text-To-Speech (Tts)Usaspending
What you need to know about the Seattle Tech Scene
Home to tech titans like Microsoft and Amazon, Seattle punches far above its weight in innovation. But its surrounding mountains, sprinkled with world-famous hiking trails and climbing routes, make the city a destination for outdoorsy types as well. Established as a logging town before shifting to shipbuilding and logistics, the Emerald City is now known for its contributions to aerospace, software, biotech and cloud computing. And its status as a thriving tech ecosystem is attracting out-of-town companies looking to establish new tech and engineering hubs.
Key Facts About Seattle Tech
- Number of Tech Workers: 287,000; 13% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Amazon, Microsoft, Meta, Google
- Key Industries: Artificial intelligence, cloud computing, software, biotechnology, game development
- Funding Landscape: $3.1 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Madrona, Fuse, Tola, Maveron
- Research Centers and Universities: University of Washington, Seattle University, Seattle Pacific University, Allen Institute for Brain Science, Bill & Melinda Gates Foundation, Seattle Children’s Research Institute
