Top Tech Jobs & Startup Jobs

Owns the architecture, deployment, security, automation, observability, and operation of large-scale Apache Kafka and Confluent environments. Responsibilities include cluster sizing, HA/DR, Kafka Connect, Schema Registry, developer enablement, troubleshooting, infrastructure as code, and collaboration with application teams. The role also involves code and design reviews, documentation, communication, and mentoring junior engineers.

Build low-latency, high-reliability trading, risk, and analytics systems for fintech applications. Translate quantitative models into production software, collaborate with quants and traders, implement market data and FIX systems, and optimize performance through concurrency, profiling, and debugging. The role also involves code and design reviews, stakeholder communication, documentation, mentoring junior engineers, and supporting risk and P&L attribution capabilities.

Design, operate, and optimize production model-serving platforms for LLMs, vision models, and recommendation systems. Responsibilities include inference performance optimization, routing, batching, caching, autoscaling, GPU utilization, observability, deployment automation, incident response, security controls, and capacity planning. The role collaborates with ML and product teams to release models and improve reliable, cost-effective AI services at scale.

Design, implement, and deploy reinforcement learning systems for real and simulated environments. Develop RL algorithms, reward functions, offline and imitation learning methods, scalable distributed training infrastructure, and safety mechanisms. Train neural network policies on GPU clusters, evaluate models against adversarial and out-of-distribution cases, monitor production behavior, and collaborate with scientists and product teams to deliver impactful RL solutions.

Operate and maintain enterprise PLM platforms, including installation, configuration, performance tuning, upgrades, migrations, integrations, high availability, and disaster recovery. Partner with engineering, manufacturing, and functional teams to ensure a reliable and secure PLM ecosystem. Required work includes database and Linux/Unix administration, middleware integration, scripting, troubleshooting, and documentation. Preferred experience includes cloud platforms, infrastructure as code, CI/CD, PLM certifications, and large-scale CAD integrations.

Design, train, evaluate, and deploy reinforcement learning systems for complex decision-making problems. Responsibilities include developing RL algorithms, simulation environments, reward functions, neural network policies, and scalable data collection pipelines. The role requires taking research solutions into production with emphasis on stability, safety, and continuous improvement. Candidates should bring strong theoretical and engineering expertise, experience with GPU-based training, and a record of impactful RL research or deployments.

Develop and maintain enterprise Adobe AEM digital experiences, including components, templates, workflows, Assets, headless CMS solutions, and integrations. Build Java-based solutions using OSGi, Sling Models, HTL, and Servlets; optimize performance, Dispatcher caching, and deployments; support CI/CD through Cloud Manager, Jenkins, or GitHub Actions; and troubleshoot production issues while collaborating with cross-functional teams.

Build and operate petabyte-scale data pipelines for AI training, evaluation, and continual improvement. Responsibilities include multimodal data ingestion, cleaning, deduplication, labeling, dataset versioning, lineage, privacy enforcement, high-throughput GPU data loading, observability, storage optimization, and data quality management. Collaborate with ML researchers and engineers to improve model training efficiency and reproducibility.

Designs and maintains large-scale Terraform infrastructure-as-code across cloud and hybrid environments. Responsibilities include building reusable modules, automating CI/CD pipelines, enforcing policy-as-code, managing Terraform state, supporting multi-account and multi-cloud provisioning, testing infrastructure, embedding security guardrails, migrating legacy infrastructure, optimizing costs, documenting platform standards, and mentoring engineering teams.

Architects, deploys, and operates secure, resilient OCI environments, including landing zones, networking, IAM, compute, storage, databases, Kubernetes, CI/CD, observability, disaster recovery, and cost optimization. Builds infrastructure-as-code and automation with Terraform, Python, and Bash; strengthens cloud security; advises application teams; troubleshoots incidents; and mentors junior engineers.