What We're Looking For

As a Machine Learning Solutions Engineer, you will operate at the intersection of machine learning, distributed systems, and cloud infrastructure.
You will partner with customers to design and deploy end-to-end AI systems, spanning:

• Model development and training
• GPU infrastructure and cluster design
• Distributed inference and production deployment

This role goes beyond traditional ML solutions engineering—you will act as a technical architect, helping customers make critical decisions across compute, orchestration, and system design.

The role can be based out of our New York City or San Francisco office, with an in-office requirement of at least 2-3 days per week and occasional team and company offsites. We are not able to provide visa sponsorship for this role at this time. The annual base pay range for this role is $150,000 - $195,000, in addition to a variable pay component and meaningful equity. 

What You’ll Do

Customer Architecture & Technical Leadership

• Partner with customers to understand ML workloads, infrastructure constraints, and scaling requirements
  
  
• Architect end-to-end solutions across:
  
  
• Data pipelines (CPU → GPU workflows)
  
  
• Distributed training (multi-node, multi-GPU)
  
  
• High-throughput inference systems
  
  
• Translate business goals (latency, cost, throughput) into technical system design decisions
  
  

GPU & Infrastructure Design

• Design and optimize workloads across GPU clusters (H100, H200, B200, etc.)
  
  
• Advise on:
  
  
• Training vs inference cluster design
  
  
• Interconnect choices (Ethernet vs Infiniband / RDMA vs Roce)
  
  
• Storage strategies (local NVMe vs networked / object storage)
  
  
• Model and optimize for:
  
  
• Tokens/sec, tokens/$
  
  
• Throughput vs latency tradeoffs
  
  
• GPU utilization and scheduling efficiency
  
  

Kubernetes & Platform Systems

• Design and support deployments on Kubernetes (EKS, GKE, on-prem clusters)
  
  
• Work with:
  
  
• GPU scheduling (time-slicing, MIG, bin-packing)
  
  
• Autoscaling and workload orchestration
  
  
• Helm-based deployments and multi-tenant environments
  
  
• Help customers balance:
  
  
• Raw Kubernetes flexibility vs platform abstraction (Lightning)
  
  

Demos, POCs, and Execution

• Build and deliver technical demos and POCs that showcase:
  
  
• Distributed training workflows
  
  
• Scalable inference endpoints
  
  
• End-to-end ML pipelines on Lightning AI
  
  
• Scope and lead POCs aligned to customer success metrics (latency, cost, reliability)
  
  

Cross-Functional Impact

• Act as the bridge between customers, product, and engineering
  
  
• Provide feedback on:
  
  
• Platform gaps in infrastructure, orchestration, and performance
  
  
• Emerging patterns in GPU usage and distributed systems
  
  
• Influence roadmap across ML workflows and infrastructure capabilities
  
  

Enablement & Thought Leadership

• Create technical content
• Architecture guides (e.g., high-throughput LLM inference systems)
• Best practices for GPU utilization and scaling
• Educate customers on modern AI infrastructure patterns

What You’ll Need

ML + Systems Expertise

• 3–6+ years experience in:
  
  
• Machine Learning / AI Engineering
  
  
• Solutions Engineering / Sales Engineering / ML Consulting
  
  
• Strong understanding of:
  
  
• Training vs inference workloads
  
  
• Model optimization (quantization, batching, caching, etc.)
  
  

GPU & Distributed Systems

• Experience working with:
  
  
• GPU clusters (NVIDIA stack preferred)
  
  
• Distributed training or inference systems
  
  
• Familiarity with:
  
  
• NCCL, CUDA, or GPU performance profiling
  
  
• Networking concepts (RDMA, Roce, Infiniband, high-throughput systems)
  
  

Kubernetes & Cloud Platforms

• Hands-on experience with:
  
  
• Kubernetes (EKS, GKE, or on-prem)
• Slurm 
• Containerization (Docker)
  
  
• Exposure to:
  
  
• GPU scheduling in Kubernetes environments
  
  
• Multi-tenant or production ML deployments
  
  

Programming & Tooling

• Strong Python skills (PyTorch preferred)
  
  
• Experience building:
  
  
• ML pipelines
  
  
• APIs or inference services
  
  
• Familiarity with Lightning AI, PyTorch Lightning, or similar frameworks is a plus
  
  

Customer-Facing Excellence

• • Ability to:
    
    
    • Explain complex infrastructure and ML tradeoffs clearly
      
      
    • Run technical discovery and uncover quantifiable success metrics
      
      
  • Experience working cross-functionally with:
    
    
    • Sales, product, and engineering teams

What We're Looking For

We are looking for an Account Executive with experience selling highly technical, developer-focused products to CTOs, VPs of Engineering, software engineers, researchers, and/or data scientists. You thrive in a fast-paced, start-up environment focusing on every step of the sales process, from prospecting, qualifying, and nurturing leads to running demos, negotiating contracts, and closing deals. We want someone who thinks about how to uncover and address our customers’ problems to drive customer acquisition while feeding their requirements back to inform the product roadmap.

This role is based out of our New York City office, with an in-office requirement of at least 3 days per week and occasional team and company offsites.

What You’ll Do

• Build an understanding of our target markets, value proposition, and pricing models to not only meet but exceed quarterly revenue targets.
• Focus on high-quality, consistent outbound prospecting across key market segments to build the sales pipeline and optimize the customer funnel.
• Qualify and develop both inbound and outbound sales leads.
• Collaborate with the product, engineering, and marketing teams to continuously improve and iterate on the sales process.
• Analyze industry trends and customer segmentation to identify and capitalize on new sources of qualified leads.
• Work alongside the marketing team to increase the number and quality of inbound leads.
• Champion data integrity and accuracy using HubSpot to track activity and manage sales opportunities through the funnel.

What You’ll need

• 5+ years of experience as an Account Executive or in a similar sales role, selling technical or developer-focused products to technical audiences.
• Familiarity with the machine learning, AI, or software development ecosystem, and an ability to grasp complex technical concepts.
• Proven track record of meeting or exceeding revenue targets in a fast-paced startup environment.
• Experience with outbound prospecting, qualifying leads, running demos, and closing deals is essential.
• Ability to uncover customer pain points, articulate value propositions, and effectively address objections to drive solutions.
• Strong interpersonal skills to work cross-functionally with leadership, product, engineering, and marketing teams.
• Proficiency with HubSpot or a similar CRM to track activity, manage the sales pipeline, and ensure data integrity.
• Solid understanding and application of a sales methodology (e.g., MEDDIC, Challenger, or Sandler) with the ability to tailor approaches to different customer needs and scenarios.

Compensation

This role offers $300K OTE, with a 50/50 base/variable split, in addition to meaningful equity. 

What We're Looking For

We are seeking a driven, goal-oriented, and quick-learning Sales Development Representative (SDR) to join our team. In this role, you'll be at the forefront of generating new business opportunities by engaging with prospective clients and building a robust sales pipeline. You'll work closely with the team to identify, qualify, and nurture leads, ensuring a seamless handoff to our account executives. This will be an outbound role with a heavy emphasis on prospecting.

This role is based out of our New York City office, with an in-office requirement of at least 4 days per week and occasional team and company offsites.

What You’ll Do

• Become an expert on our sales process with an in-depth understanding of our target markets, value proposition, and pricing models to not only meet but exceed both quarterly and annual goals.
• Focus on high-quality, consistent outbound prospecting across all market segments to build the sales pipeline and optimize the customer funnel.
• Qualify and develop outbound sales leads.
• Collaborate with the sales and marketing teams to build and optimize email campaigns with targeted messaging for specific user personas and improve the lead qualification process.
• Analyze industry trends and customer segmentation to identify and capitalize on new sources of qualified leads.
• Utilize a CRM system to track activity and manage sales opportunities.

What You’ll Need

• 1-3 years of experience in sales development, business development, or a similar role, preferably within the tech or AI industry.
• Proven track record of meeting or exceeding sales targets through outbound prospecting and lead generation efforts.
• Strong understanding of sales processes and CRM tools (experience with Salesforce or HubSpot is a plus).
• Excellent communication and interpersonal skills, with the ability to craft persuasive messaging and build rapport with prospective clients.
• Highly organized and detail-oriented, with the ability to manage multiple tasks and priorities in a fast-paced environment.
• Self-motivated and driven, with a passion for learning and continuous improvement.
• Team-oriented mindset, with the ability to collaborate effectively with cross-functional teams, including marketing, sales, and customer success.
• A goal-oriented attitude, with a strong desire to grow within a dynamic, high-growth company.

Compensation

The base salary range for this role is $60,000-$80,000, in addition to a variable component and meaningful equity.