The Role

As Director, AI Data Operations, you will own the people and operational backbone of a 50+ person team that powers data operations for AiDASH’s proprietary models — across model quality control for customer deliveries, training data generation for AI models, and multi-modal imagery sourcing. The team’s work directly determines the quality of our models, the rate at which our models improve, and what we ship to customers. 

Reporting directly to VP, Product & Process Excellence; you will lead this team through a major transformation — from manual operations to AI-augmented operations — while raising the bar on quality, ownership, and execution. You will thrive in this role if you have run annotation pipelines, training data workflows, or model quality control operations, ideally in an AI product company — and you are ready to bring that experience to a domain where the stakes are high and the work has real-world consequences. 

How you'll make an impact:

• Lead, inspire, and scale a 50+ person team — establishing clear accountability, operational discipline, and a high-ownership culture 
• Drive operations against defined quality benchmarks and efficiency targets (e.g. QC accuracy, delivery turnaround time, on-time delivery, throughput, and cost efficiency)
• Drive image sourcing strategy — keeping abreast of industry trends, finding new vendors, managing commercial relationships, and managing image acquisition 
• Drive an AI-first transformation of the function — pilot and embed AI agents / LLMs, and modern tooling that fundamentally shifts how the work gets done 
• Build and implement repeatable processes, playbooks, and staffing strategies to ensure the organization runs efficiently in an AI-first manner 
• Develop and retain top operational talent 
• Collaborate & partner globally with with India and US based R&D teams— data science, platform engineering, product management — and with Customer Success teams to align operations with model training needs and customer commitments 

What we're looking for:

• A senior operations leader (12+ years, 5+ managing 50+ headcount) who has built and run quality-critical operations at scale, preferably with experience of annotation/ML data ops 
• Manager-of-managers credentials, with credibility across technical, product, and senior leadership 
• Passionate about driving operational excellence and using AI to reshape work; hands-on experience leading AI-led transformations, even if smaller-scale or in progress. We care about your conviction, AI fluency, and pattern recognition. This is a core requirement for the role 
• A track record of building high-ownership cultures in operational functions 
• A high-quality bar and strong operating discipline — metrics, SLAs, and rhythms are how you run 

Good to have 

• Background in GIS, remote sensing, satellite imagery, or geospatial data
• Experience with annotation operations or imagery and data vendor procurement

 What you'll love:

• Leading one of the largest and strategically important teams at AiDASH 
• A real mandate to transform an operational function with AI 
• Working alongside high-caliber peers who value ownership, low ego, and measurable impact
  

What This Role Is Not 

• ❌ A data engineering or analytics role — you won't be building data platforms, dashboards, or BI pipelines; you'll be running the operations – people, process, vendors - that determine the quality of our AI models 
• ❌ A digital transformation consulting role — this isn't a strategy-and-handoff engagement; you'll own execution and be accountable for what ships to customers 
• ❌ A program management role — you won't be tracking milestones and sending status updates; you'll be setting the bar for quality and driving the team to hit it 
• ❌ A senior individual contributor role — you'll lead a 50+ person team through significant change; what matters most isn't what you can do yourself, but what you can get a team to do together. 

In Summary 

This role is about people leadership, operational excellence, and leading the AI transformation of a function where precision, ownership, and quality are everything. If you love running great teams, setting a high bar, and are excited to use AI to reshape how operational work gets done, this is your role. One requirement: you've worked close to the model — in annotation pipelines, training data workflows, or quality operations — rather than in data analytics, BI, or IT services delivery.

We are proud to be an equal-opportunity employer. We are committed to embracing diversity and inclusion in our hiring practices, and we promote a work environment where everyone, from any race, color, religion, sex, sexual orientation, gender identity, or national origin, can do their best work. 

The Role

As a Staff Product Designer at AiDASH, you will define the standard for AI-augmented design practice across the organization. You are not just a designer who occasionally uses AI—you are someone who has fundamentally rewired your design workflow around AI tools, using them daily for research synthesis, rapid prototyping, visual exploration, and production-ready output. 

You bring extensive experience in user experience design with deep specialization in at least three areas: user research, service design, digital product design, interface design, visual design, or related disciplines. Crucially, you also bring a proven track record of leveraging AI tools to dramatically accelerate and elevate your design work. 

How you'll make an impact:

• Drive Technology Transformation: Play a key role in delivering and designing technology solutions that reshape how our clients operate. Use AI tools (e.g., Galileo AI, Uizard, Relume, v0, or similar) to go from concept to interactive prototype in hours, not days—dramatically accelerating ideation-to-delivery timelines. 

• Collaborate Across Teams: Work closely with cross-functional teams to produce design deliverables—journey maps, service blueprints, roadmaps, prototypes, and design systems.  

• Apply Research with Precision: Use diverse research methods—context analysis, moderated interviews, experiments, and user testing. Augment these with AI to transcribe interviews, cluster findings, extract patterns from qualitative data, and accelerate insight generation and communication. 

• Create Production-Ready Designs with AI: Use generative AI for mood boards, visual explorations, icon generation, illustration, and design variations at scale. Craft effective prompts to get high-quality outputs from AI design and image-generation tools, then iterate and refine AI-generated assets to production quality. 

• Build and Scale AI-Augmented Design Systems: Use AI to help maintain, scale, and enforce consistency across design system components and documentation. Identify and implement AI-powered automations to eliminate repetitive tasks (e.g., auto-generating responsive variants, batch-resizing assets, content population). 

• Champion AI Adoption in Design: Evangelize and mentor the broader design and product team on integrating AI tools into their workflows. Establish best practices, standards, and playbooks for AI-assisted design across the organization. 

• Manage Scope, Risks, and Progress: Proactively monitor project scope, risks, and updates, ensuring clear communication and alignment across stakeholders throughout the project lifecycle. 

Minimum Qualifications:

• Bachelor’s degree in Design, HCI, a related field, or equivalent practical experience 

• 6+ years of experience in UX/product design with a strong portfolio showcasing design principles applied to web and/or mobile platforms 

• Demonstrated, hands-on proficiency with AI design tools—must be able to show examples of AI-assisted work in your portfolio (e.g., AI-generated prototypes, AI-enhanced visuals, AI-driven research synthesis) 

• Proficiency with core design tools: Figma (required), plus experience with at least two AI-powered design or prototyping tools 

• Strong understanding of when to use AI and when human craft is essential—you know AI’s strengths and limitations in a design context 

Preferred Qualifications:

• Experience with AI prototyping tools such as Galileo AI, Uizard, Relume, v0 by Vercel, Framer AI, or Figma AI features 

• Familiarity with generative image tools (Midjourney, DALL-E, Stable Diffusion, Adobe Firefly) for design exploration and asset creation 

• A highly creative mindset with the ability to translate ideas into polished, functional, and visually compelling prototypes—with or without AI assistance 

• Proven success collaborating across organizational boundaries and working effectively with cross-functional teams in fast-paced startup environments 

• Strong verbal and written communication skills, including the ability to craft and deliver engaging presentations 

• Passion for climate tech, sustainability, or infrastructure modernization 

PORTFOLIO REQUIREMENTS 

Your portfolio should include at least two case studies that explicitly demonstrate your use of AI tools in the design process. We want to see: 

• Before/after examples showing how AI accelerated or improved your workflow 

• Your process for integrating AI—what tools you used, how you prompted them, and how you refined the outputs 

• Clear articulation of where AI added value vs. where your human judgment and craft were essential 

We’re not looking for perfection in AI output—we’re looking for a designer who knows how to wield AI strategically and isn’t afraid to show the messy, iterative process. 

The Role

We’re looking for a seasoned Staff Machine Learning Engineer to shape and scale the backbone of our production ML ecosystem. In this role, you will architect high-performing ML systems that power our geospatial intelligence platform, transforming large-scale satellite and aerial imagery into actionable insights. You’ll lead end-to-end ownership—from model deployment and MLOps to infrastructure design—while partnering closely with data science, platform engineering, and product teams to deliver reliable, scalable, and cost-efficient ML solutions. If you thrive at the intersection of deep technical expertise, system design, and cross-functional collaboration, this role is for you.

How you'll make an impact:

ML System Architecture & Production Deployment

• Design, build, and maintain end-to-end ML pipelines for batch processing of satellite and aerial imagery
• Deploy and scale ML models in production on AWS infrastructure, leveraging services like SageMaker, Bedrock,or custom-built solutions
• Implement MLflow for experiment tracking, model versioning, and model registry management
• Architect batch inference systems optimized for throughput and cost-efficiency
• Work with geospatial data formats and coordinate reference systems
• Collaborate with data scientists to transition models from research to production
• Partner with platform engineering to build scalable compute, GPU clusters, and storage layers

ML Operations & Reliability

• Implement comprehensive model monitoring systems to track performance degradation and data drift
• Design and execute canary deployments and A/B testing frameworks for safe model rollouts
• Build active learning pipelines to continuously improve model performance with minimal labeling effort
• Establish model evaluation frameworks and performance benchmarking processesCreate alerting and observability systems for production ML workloads

Technical Leadership

• Mentor ML engineers and data scientists on best practices for production ML
• Drive technical decision-making on ML infrastructure and tooling
• Collaborate with platform and data engineering teams to optimize the ML stack
• Establish engineering standards and contribute to architectural roadmaps

What we’re looking for:

• 5+ years of experience in machine learning engineering with 2+ years in a senior or lead capacity
• Proven track record deploying and maintaining ML systems in production using AWS services (SageMaker,Lambda, ECS/EKS, S3, etc.)
• Strong hands-on experience with tools like MLflow, WandB, or similar for experiment tracking and model management
• Deep expertise in image segmentation and computer vision techniques using frameworks like PyTorch or TensorFlow
• Production experience with ensemble models (xgboost, lightgbm, RF)

ML Operations Expertise

• Experience implementing model monitoring, drift detection, and alerting systems
• Hands-on experience with canary deployments, A/B testing and Shadow deployments for ML models
• Knowledge of active learning strategies and human-in-the-loop ML systems
• Strong understanding of model evaluation metrics, bias detection, and performance analysis

Technical Skills

• Expert-level Python programming with ML libraries (scikit-learn, PyTorch/TensorFlow, NumPy, pandas, etc)
• Experience with distributed batch processing frameworks (Airflow, Step Functions, Argo Workflows, Spark,Dask, Ray or similar)
• Proficiency with AWS ML ecosystem and infrastructure-as-code (Terraform, CloudFormation)
• Hands-on experience with dataset versioning tools such as DVC, LakeFS, Delta Lake, Quilt, or Pachyderm
• Strong software engineering fundamentals: unit/integration testing, CI/CD, version control, observability, designpatterns
• Experience with containerization (Docker, Kubernetes) for model deployment
• Good to have experience with ML Orchestration tools like Kubeflow, Vertex AI, etc
• Nice to have experience with GPUs: scheduling GPU jobs, optimizing GPU performance, memory profiling

We are proud to be an equal-opportunity employer. We are committed to embracing diversity and inclusion in our hiring practices, and we promote a work environment where everyone, from any race, color, religion, sex, sexual orientation, gender identity, or national origin, can do their best work.

The Role

As a SDE - 3 Platform Engineer at AiDASH, you’ll design, develop, and deploy scalable distributed systems that power our AI-driven platforms. You will build robust backend services, automated data pipelines, and analytical tools to deliver actionable insights for business-critical decisions. Partnering with product, data, and design teams, you’ll own solutions end-to-end — from system design to production deployment. Your expertise in microservices, Python, SQL/NoSQL, and cloud-native technologies (AWS, Docker, Kubernetes) will help evolve our architecture as we scale. Beyond coding, you’ll drive engineering excellence through code reviews, refactoring, and performance optimization, while mentoring peers and fostering reusable, reliable system design. If you thrive in solving complex challenges, love automation, and want to shape systems that make industries climate-resilient, this role is for you.

How you'll make an impact: