AI/ML & Algorithm Engineer

• Design and implement production multi-agent AI systems: agent coordination, tool use, context and memory management, structured output, and human-in-the-loop ratification loops.
• Develop novel algorithms for scoring, ranking, prioritization, and optimization - including multi-dimensional impact scoring systems that rank ideas or proposals by value, feasibility, revenue potential, and strategic alignment.
• Build LLM-powered workflows: retrieval-augmented generation (RAG), prompt pipelines, fine-tuning, structured extraction, and domain-adapted language models for enterprise contexts.
• Architect closed-loop AI systems where agent observations feed structured proposals for human review and ratification, then feed back into continuous improvement cycles.
• Identify novel algorithmic and AI system designs that represent patentable inventions; author invention disclosures and collaborate with patent counsel through prosecution.
• Lead evaluation and benchmarking of AI model performance in production: accuracy, latency, cost, reliability, and domain-specific accuracy metrics.
• Drive build-vs-buy-vs-partner decisions for AI components; design integration patterns for third-party foundation models, AI APIs, and specialized ML services.
• Establish AI governance practices: model cards, explainability tooling, bias evaluation, auditability, and responsible deployment standards.
• Design AI and agent systems that operate across decentralized, federated data domains - enabling intelligent query routing, context assembly, and inference across disparate operational data sources without requiring centralized data pipelines; architect retrieval and grounding strategies that respect data sovereignty and domain ownership as the organization transitions from siloed data stores to a federated intelligence layer.

Do you have experience in System performance monitoring?, * 8+ years in AI/ML engineering or research, with at least 3 years building and operating production AI systems at a senior IC level.

• Deep expertise in large language models and agentic frameworks (LangChain, LangGraph, AutoGen, CrewAI, or equivalent); strong understanding of prompt engineering and model behavior.
• Proven ability to develop novel algorithmic approaches - not just apply existing frameworks - and document them rigorously for IP purposes.
• Strong ML fundamentals: optimization theory, probabilistic modeling, statistical learning, reinforcement learning, and deep learning architectures.
• Proficiency in Python and at least one deep learning framework (PyTorch or JAX); familiarity with ML infrastructure (MLflow, Weights & Biases, Ray, or equivalent).
• Experience with vector databases, embeddings, semantic search, and knowledge graph architectures as components of production AI systems.
• Demonstrated ability to deploy and maintain AI systems in production: monitoring, versioning, rollback strategies, and performance degradation detection., * Named inventor on AI, ML, or algorithmic patents.
• Experience with autonomous AI systems, robotic process automation, or AI applied to physical infrastructure, industrial operations, or IoT environments.
• Familiarity with RLHF, Constitutional AI, or other alignment and fine-tuning methodologies.
• Experience with digital twin architectures, simulation environments, or AI-driven 3D modeling tools in operational contexts.
• Background in algorithm design for scheduling, resource allocation, combinatorial optimization, or operational research.
• Experience building AI systems that process structured operational data: time-series sensor readings, maintenance logs, energy consumption data, or workforce telemetry.
• Familiarity with federated learning frameworks or privacy-preserving ML techniques that enable model training across distributed, domain-owned data sources without centralizing sensitive operational data.
• Experience integrating AI agents with federated data access layers - query routing across multiple source systems, semantic data discovery, and context-aware retrieval from heterogeneous operational datastores.
• Graduate degree (MS or PhD) in Computer Science, Machine Learning, Mathematics, or a related quantitative field.

If you are a motivated and results-driven individual with a passion for data center services and a knack for building strong client relationships, we want to hear from you. Join us in revolutionizing the data center industry and apply today!

3.53.5 out of 5 stars United States Remote From $200,000 a year - Full-time, Pulled from the full job description

• AD&D insurance
• Parental leave
• Health insurance
• 401(k) matching
• Paid time off
• Vision insurance
• Health savings account, The base salary range for this role starts at $200,000 per year. This reflects a good-faith estimate of what we reasonably expect to pay upon hire, based on factors such as skills, experience, education, and market/location. Our comprehensive benefits include health, dental, and vision insurance, Health Savings Account (HSA), gym discount, mental health, Discounted Group Life & AD&D, Discounted Group Short & Long-term Disability, 401(k) retirement matching, PTO/paid holidays, and parental leave. Final compensation will be determined by job-related factors consistent with applicable law.

Salute is a leading provider of cutting-edge Data Center Infrastructure Services, dedicated to serving data center clients worldwide. We pride ourselves on delivering sustainable solutions, unparalleled reliability, and outstanding customer service. As we continue to grow, we are seeking a dynamic and experienced AI/ML & Algorithm Engineer to join our team and drive our relationships with hyperscale clients to new heights.