Implements machine learning model serving for production, automates workflows, develops infrastructure and tools, and collaborates with stakeholders to integrate models into systems.
Compensation
US: Hiring Range in USD from: $87,800 to $209,500 per annum. May be eligible for bonus and equity.
Responsibilities
Implements machine learning model serving for production
Ensures readiness of models for deployment
Automates model serving workflows
Creates infrastructure and frameworks to monitor performance
Evaluates data quality, security, and privacy issues
Partner with Account Executives through the full sales cycle: discovery, solutioning, demos, proof of concepts, RFP responses, and handoff to the implementation team
Run structured discovery conversations that uncover the business value a prospect has not yet articulated for themselves, in their data, workflows, or current tech stack, and build that into a clear value case
Design and deliver product demonstrations that walk a prospect from that value case straight into the platform mechanics that deliver it, showing exactly how MoEngage's core capabilities and AI decisioning engine get them there
Lead technical validations and proof of concepts that prove out the value case with the prospect's own data, working with engineering and solutions architecture where needed
Write clear, accurate responses to RFPs and RFIs, including technical architecture and integration questions
A highly hands-on technical leadership role focused on translating product ideas and data science capabilities into production-ready AI solutions, specifically within LATAM.
Compensation
Total monthly compensation: $3,500—$4,500 USD
Responsibilities
Lead the technical design and implementation of AI-powered product features from concept through production.
Own end-to-end architecture for AI solutions, including data flows, model integration, APIs, and application integration.
Make pragmatic decisions to accelerate delivery while maintaining system integrity.
Ensure AI solutions are secure, observable, scalable, and aligned with platform standards.
Act as the technical lead for a cross-functional AI Pod.
Requirements
BS or MS in Computer Science, Engineering, or related technical field
A Data/AI Developer focused on building and validating ML models for supply chain forecasting, developing LLM workflows, and managing MLOps on Databricks.
Compensation
The suggested pay for this position ranges from $95,546 to $105,875. The actual salary offer will carefully consider a wide range of factors, including your skills, qualifications, and location. Also, certain positions are eligible for additional forms of compensation, such as bonuses.
Responsibilities
Build and validate ML models for inventory and demand forecasting, and document model validation.
Automate identification and validation of product substitutions during supply disruptions.
Build LLM and agentic workflows inside a governed, auditable AI operating model.
Run MLOps on Databricks (MLflow, model serving, monitoring).
Deliver dashboards and analytics for supply chain stakeholders.
Requirements
Bachelor's degree in computer science, data science, statistics or a related field
Lead AI/ML platform engineering and cloud security across Azure and GCP, owning Kubernetes, CI/CD, data fabric pipeline, and vendor handover for GSK's AI security initiatives.
Locations (3)
Bengaluru, Karnataka, India
United Kingdom
United States
Responsibilities
Own the AKS and GKE clusters, GPU node pools and model-serving tier
Lead engineering delivery of the data fabric pipeline
Own Kubernetes and container orchestration for AI and ML workloads
Own CI/CD pipelines for AI and ML delivery
Own data ingestion and transformation layers
Requirements
Bachelor's degree in a relevant discipline or equivalent professional experience
The Senior Developer, AI is responsible for designing, developing, deploying, and supporting enterprise AI solutions including scalable AI applications, AI agents, and RAG solutions using Databricks.
Responsibilities
Design, build, test, deploy, and support scalable enterprise AI applications, AI agents, and intelligent workflows using Databricks and cloud-native technologies.
Develop AI agents, multi-agent workflows, and RAG solutions by integrating enterprise data, APIs, tools, and business processes to enable automation and decision support.
Create APIs, backend services, integrations, and reusable frameworks while applying software engineering best practices such as CI/CD, automated testing, monitoring, and secure deployment.
Drive solution reliability, performance, Responsible AI compliance, data governance, operational readiness, and continuous improvement through testing, evaluation, and technical reviews.
Partner with business stakeholders, Product Owners, Architects, Data Scientists, Data Engineers, platform teams, and vendors while providing technical guidance, knowledge sharing, and mentoring across AI Delivery PODs.
Lead the commercial and technical strategy for CoreWeave’s inference offerings across the AMER region, driving new customer wins, shaping product roadmap, and translating customer needs into product feedback.
Locations (6)
Bellevue, Washington, United States
Dallas, Texas, United States
Livingston, New Jersey, United States
Manhattan, New York, United States
San Francisco, California, United States
Senior Principal Chief Architect -Enterprise Platform/Distributed AI Infrastructure & Kubernetes/PyTorch
Lead the Forward Deployed Engineering function for APAC AI Center of Excellence, architecting hybrid cloud AI platforms and driving open‑source community engagement.
Responsibilities
Orchestrate the Forward Deployed Engineering squad and set technical strategy
Drive end‑to‑end technical strategy for large‑scale hybrid cloud AI deployments
Design complex integration layers for client platforms
Act as primary technical bridge to global product and ecosystem engineering hubs
Maintain community‑first mindset and contribute to open‑source foundations
The base salary range for this role is $177,000 to $237,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).
Responsibilities
Serve as the AMER field's primary intelligence source on AI inference
Drive commercial and technical strategy in AMER for net new customer wins
Identify new business opportunities in AMER
Develop deep expertise across the AI runtime landscape
Translate customer requirements into product feedback
Requirements
Advanced degree in Computer Science, Machine Learning, or Engineering
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