Software Gigs

Sr. Director role overseeing SIE's data and AI platform ecosystem, including data infrastructure (streaming, ingestion, warehouse), experimentation platforms, and governance tools. Responsible for defining long-term vision, leading global engineering teams, and ensuring platforms process massive data volumes to deliver insights across gaming, content creation, and enterprise operations. Must drive scalability, cost efficiency, security, and operational excellence while collaborating with senior leadership to align platform strategy with business objectives. Requires proven Sr. Director-level experience and thought leadership in platform architecture, real-time data processing, and ML/AI integration.

The Applied AI Engineer develops, deploys, and maintains generative AI solutions for insurance products and internal workflows. The role involves implementing end-to-end AI pipelines using AWS services (SageMaker, Lambda, ECS/EKS, S3), building feature engineering workflows in Snowflake, and collaborating with cloud and MLOps teams. Candidates need 3+ years of AI/ML engineering experience with 1–2 years focused on generative AI or LLMs, proficiency in Python and frameworks like PyTorch or Hugging Face Transformers, and hands-on cloud deployment experience. The position requires monitoring model performance, ensuring security and compliance, and supporting AI architecture reviews.

Design and build large-scale multimodal foundation models that integrate high-dimensional biomedical imaging with molecular and language data. You will implement cross-domain data fusion strategies, develop high-performance ML pipelines for petabyte-scale datasets, and collaborate with scientists and engineers to translate biological complexity into scalable, production-ready code. The role requires deep expertise in Computer Vision architectures, distributed training frameworks, and expert Python proficiency. You will contribute through high-impact publications or open-source work and demonstrated ability to handle the noise and sparsity inherent in biological data.

Qualcomm seeks a Machine Learning R&D leader to design and deliver Agentic AI systems for hardware design automation. The role combines hands-on technical execution with team leadership, requiring deep expertise in generative AI, large language models, and ML/AI product development. Responsibilities include architecting end-to-end ML solutions, coaching an interdisciplinary team of researchers and engineers, and bridging research prototypes into production design tools. The ideal candidate brings PhD-level credentials, 2+ years of industry ML/GenAI experience, and proven expertise in agentic AI frameworks, foundation models, and complex ML software pipelines.

Lead technical delivery of complex autonomy capabilities for Shield AI's V-BAT and X-BAT unmanned aircraft platforms, spanning mission autonomy, payload integration, flight-control interfaces, and multi-agent behaviors. Own end-to-end integration from architecture through field deployment, coordinate across Aircraft, Autonomy Capabilities, Perception, and GCS teams, and drive mission readiness for customer releases. Mentor engineers, improve engineering practices, and serve as primary technical partner to the Aircraft team on integration approaches and interface design. Requires 7+ years of relevant experience, expert C++ and Linux development, and deep expertise in complex autonomy systems or embedded systems integration.

Lead the entire engineering team at a VC-backed AI trading firm, combining hands-on ML research and model development with technical leadership. Own the end-to-end development of production AI systems deployed in live financial markets, including model design, training, evaluation, and infrastructure. Set technical direction across ML and software engineers, drive hiring and team development, and translate research into measurable real-world trading performance. Require 5–8 years of applied ML/AI experience with 3+ years managing full engineering teams.

As a Security Controls Assessor, you will design, implement, and manage policies and procedures to ensure database and software security while assessing security controls within operational systems (both OT and IT). You will review technical implementations across disparate systems including cloud, hybrid, virtualization, and AI/ML solutions, and communicate findings regarding control implementation and system security impact. This role requires 14+ years of cybersecurity experience, deep knowledge of NIST SP 800-53 and DoD Risk Management Framework, and the ability to work independently on highly complex problems while maintaining professional judgment under pressure.

Design, develop, and deploy end-to-end generative AI solutions including GenAI agents, LLMs, and applications to solve complex business challenges. Build data pipelines, design APIs for AI accessibility, and collaborate with cross-functional teams (developers, data scientists, business) to implement enterprise GenAI solutions. Requires 4+ years of full-stack application development (Java, Python, JavaScript) and 3+ years with data structures, algorithms, and data stores. Stay current with AI research and communicate technical concepts to non-technical stakeholders.