Technical Support Engineer (Inference) - India Weekends

About the Role As a Customer Support Engineer at a pioneering AI company, you'll be the first line of defense to support customers as they build out training, fine tuning, and inference solutions with Together AI. You'll dive deep into complex technical challenges, providing swift and effective solutions while serving as a product expert. As a part of the Customer Experience organization, you will collaborate closely with product and sales, driving continuous improvement of our offerings. This is an exciting opportunity for a deeply technical professional passionate about AI and customer success to make a significant impact in a fast-paced, innovative environment. Responsibilities Engage directly with customers to tackle and resolve complex technical challenges involving our cutting-edge Kubernetes GPU clusters; ensure swift and effective solutions every time. Become a product expert in our GPU Cluster service, serving as the last line of technical defense before issues are escalated to Engineering and Product teams. Collaborate seamlessly across Engineering, Research, and Product teams to address customer concerns; collaborate with senior leaders both internally and externally to ensure the highest levels of customer satisfaction. Transform customer insights into action by identifying patterns in support cases and working with Engineering and Go-To-Market teams to drive Together’s roadmap (e.g., future models to support) Maintain detailed documentation of system configurations, procedures, troubleshooting guides, and FAQs to facilitate knowledge sharing with team and customers. Be flexible in providing support coverage during holidays, nights and weekends as required by business needs to ensure consistent and reliable service for our customers. Requirements 3+ years of experience in a customer-facing technical role with at least 1 year in a support function in AI or supporting a mission-critical API in SaaS Strong technical background, with knowledge of AI, ML, GPU

About the role As a Technical Support Engineer at a pioneering AI company, you'll be the first line of defense to support customers as they build out training, fine tuning, and inference solutions with Together AI. You'll dive deep into complex technical challenges, providing swift and effective solutions while serving as a product expert. As a part of the Customer Experience organization, you will collaborate closely with product and sales, driving continuous improvement of our offerings. This is an exciting opportunity for a deeply technical professional passionate about AI and customer success to make a significant impact in a fast-paced, innovative environment. Responsibilities Triage and respond to inbound support tickets across self-serve and enterprise customers using a support/CRM platform; identify patterns in ticket clusters (e.g., a wave of the same error code), surface them to engineering with context and affected case lists, and follow through to resolution. Draft clear, accurate status updates and maintenance notifications for customers during planned maintenance windows or incidents; communicate expected impact without exposing internal platform details. Collaborate seamlessly across Engineering, Research, and Product teams to address customer concerns; collaborate with senior leaders both internally and externally to ensure the highest levels of customer satisfaction. Answer customer questions about the platform's API, model/fine-tuning workflows, model availability, and deployment/endpoint configuration; reproduce reported errors to confirm expected vs. broken behavior and provide actionable next steps. Provision and configure SSO connections for enterprise customers (Google Workspace, Okta, Azure AD, etc.); guide customers through IdP-side setup steps; diagnose login failures by cross-referencing the platform's identity provider configuration against the customer's; escalate confirmed platform-side gaps. Triage customer billing questions using bill

Role: Application Reliability Engineer Location: Gurgaon Who we are Graviton Research Capital is a privately funded quantitative trading firm striving for excellence in financial markets research. We trade across a multitude of asset classes and trading venues using a diverse range of concepts, from time series analysis and stochastic models to machine learning and statistical inference. We analyse terabytes of data to identify pricing anomalies and drive innovation in financial markets. Key Responsibilities and Deliverables The ideal candidate will possess a strong background in technical support, with a passion for problem-solving and a commitment to excellence. As an Application Reliability Engineer, you will be responsible for: Monitor production services and respond quickly to alerts, incidents, and outages to ensure smooth operation and minimal downtime. Monitor trading systems and infrastructure., Triage issues across trading support services, databases, and infra; escalate and coordinate with the right owners, and drive root-cause analysis and ensure fixes are implemented for long-term stability. Serve as the first line of defense for trading operations. Proactively identify, address recurring issues, and build automation to reduce manual intervention. Improve observability by enhancing monitoring, logging, and alerting systems. Develop and maintain operational runbooks and SLO/SLA metrics. Eligibility and Required Skills Possess a degree in a highly analytical field, such as Engineering, or Computer Science 2-5 years of experience in Python, Shell/Bash scripting. Experience with Linux and shell/bash online tools. Hands-on experience with databases (SQL, NoSQL) Strong problem-solving and analytical skills Excellent communication skills Ability to remain calm and analytical under production pressure Good to have: Familiarity with monitoring/alerting stacks (Prometheus, Grafana, ELK, etc.) Familiarity with distributed messaging (Kafka) and caching systems (Red

A Career with Point72's Technology Team As Point72 reimagines the future of investing, our Technology group is constantly improving our company’s IT infrastructure, positioning us at the forefront of a rapidly evolving technology landscape. We’re a team of experts experimenting, discovering new ways to harness the power of open source solutions, and embracing enterprise agile methodology. We encourage professional development to ensure you bring innovative ideas to our products while satisfying your own intellectual curiosity. What you'll do Lead the design, development, and operation of scalable, enterprise-grade AI/ML architectures and systems with a strong emphasis on reliability, availability, and performance. Lead and mentor a team of engineers, driving technical direction, code quality, and iterative delivery of large-scale solutions. Partner closely with data scientists, engineers, product teams, and compliance to integrate AI/ML solutions into existing and new products. Own the end-to-end lifecycle of GenAI services, including LLM inference, model serving, and proxy/gateway layers that support multiple downstream applications. Define and uphold engineering best practices around observability, scalability, security, and cost efficiency for AI/ML platforms. Evaluate tools, technologies, and processes to ensure the highest quality and performance of AI/ML systems. Stay abreast of the latest advancements in AI/ML technologies and methodologies, and translate them into pragmatic solutions for the business. Ensure compliance with industry standards and best practices in AI/ML. What's required Bachelor's or Master's degree in Computer Science, Engineering, or a related field. 10+ years of experience in software/AI/ML engineering, with a proven track record of successful delivery of complex, production-grade systems. Demonstrated experience building large-scale enterprise-grade services with high reliability, availability, and observability (SLO/SLA-driven en

Backend Engineer (Senior Level) - SDE IV We're looking for a Senior Backend Engineer to lead the architecture and evolution of backend services that deploy and serve machine learning models in production. You'll work closely with ML Engineers, Platform, and Product teams to build scalable, reliable systems and drive technical direction across multiple teams. What You’ll Do Design and drive the long-term architecture of backend services for biometrics and ML model serving. Collaborate with core platform and backend teams on organization-wide architectural initiatives. Partner with business and engineering teams to design and deliver cross-cutting platform capabilities. Lead architectural reviews, mentor engineers, and promote engineering best practices. Build and maintain backend services for deploying and serving ML models Monitor service reliability, performance, and scalability in production Deploy and operate services on AWS using ECS + Fargate, SageMaker, or EC2 + Kubernetes Support real-time and batch inference workflows Contribute to CI/CD pipelines and deployment automation What We’re Looking For Strong expertise in backend development using Java and working knowledge of Python. Experience mentoring engineers and driving architectural decisions. Working knowledge of Python, especially for ML-related workflows Hands-on experience with AWS (e.g., DynamoDB, ECS, EC2, Redis, S3, SageMaker) Familiarity with Terraform or other infrastructure-as-code tools, and experience with CI/CD and production monitoring Experience with observability tools (Datadog, New Relic, etc.) Experience with containers and orchestration (Docker, ECS, etc.) Understanding of how ML models are deployed and served in production Experience with Kubernetes Nice to Have Experience with MLOps or ML platform engineering. Experience with asynchronous programming and event-driven systems. Jumio Values: IDEAL: Integrity, Diversity, Empowerment, Accountability, Leading Innovation Equal Opportunities :

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Key Responsibilities GenAI System Development: Design, build, and improve GenAI-powered and agentic systems supporting ASIC semiconductor engineering workflows such as code generation, data extraction, analytics, documentation automation, failure triage, root cause analysis, and technical knowledge retrieval. LLM Workflow Engineering: Build, evaluate, and optimize LLM-based workflows, including prompting, developing skills, retrieval-augmented generation (RAG and Graph-RAG), benchmarking, and quality evaluation. Machine Learning Production: Develop and implement machine learning and deep learning models for classification, regression, anomaly detection, failure analysis, and engineering decision support. Cross-Functional Collaboration: Partner with domain experts and cross-functional teams to translate complex engineering problems into scalable AI/ML and analytics solutions. Production Deployment: Support deployment, monitoring, and operationalization of AI/ML solutions in cloud and enterprise environments. Technical Communication: Communicate technical findings, recommendations, and model outcomes clearly to both technical and non-technical stakeholders. Innovation Leadership: Identify and drive high-impact o