Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube. 

Job Description:

Shield AI builds intelligent systems that protect service members and civilians. Our products include Hivemind autonomy software and V-BAT and X-BAT aircraft, and our teams support customers and operations across the United States, Europe, the Middle East, and Asia-Pacific. 

The Forward Deployed Engineer, Operations & Sustainment is a highly technical, customer-facing role focused on deploying, supporting, and sustaining Hivemind products in real operating environments. This role bridges field deployment, customer operations, technical troubleshooting, training, and sustainment. 

This is a travel-intensive role. Candidates must be willing and able to travel at least 50% of the time, including frequent domestic and international trips, customer-site work, test events, training events, and multi-week deployments as program needs require. 

In this role, you will work directly with customers and internal teams to install, configure, validate, train, troubleshoot, and support Hivemind products. The role requires strong technical judgment, clear customer communication, comfort operating under field pressure, and the discipline to turn field lessons into durable support artifacts: runbooks, supported baselines, evidence packages, known-issue records, escalation paths, customer-safe updates, and product feedback. 

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Full-time regular employee offer package:

Pay within range listed + Bonus + Benefits + Equity

Temporary employee offer package:

Pay within range listed above + temporary benefits package (applicable after 60 days of employment)

Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information.

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Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know. 

About Cantina:

Cantina is a new social platform founded by Sean Parker with the most advanced AI character creator. Our bots are lifelike, social creatures that can interact wherever people are online—across voice, video, and text. Create yourself, imagine someone new, or choose from thousands of characters to share infinitely scalable, personalized content and seamless group chat.

If you’re excited about how AI can shape creativity and social interaction, come help us build what’s next.

About the Role:

We’re looking for a Research / ML Engineer to join our Speech Team to build state-of-the-art speech systems end-to-end—from data specs through production inference. You’ll drive the model ↔ data ↔ eval flywheel for VC and adjacent tasks (controllable TTS, voice design and more), partnering closely with research, data, and infra to ship fast, reliable, and cost-aware models. In this role, you will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems.

You will thrive in this role if you:

• See research and engineering as two sides of the same coin and enjoy owning work end-to-end.

• Are results-oriented, flexible, and willing to pick up whatever moves the needle.

• Like collaborating closely with infra, data, and product to ship measurable improvements.

• Enjoy designing experiments, listening tests, and metrics that correlate with user-perceived quality.

• Eager to learn every-day, find and solve unique large-scale problems.

What You’ll Do:

• Model Building: Architect, implement, pre-train, fine-tune, and post-train/alignment (e.g., GRPO/DPO) for large-scale speech models.

• Experimental Design: Design, run, and analyze scientific experiments to advance our understanding of the models.

• Tool Development: Develop and improve dev tooling to enhance team productivity.

• Full-Stack Contribution: Contribute to the entire stack, from low-level optimizations to high-level model design.

• Data Ownership: Define data requirements and collaborate on acquisition, curation, augmentation, labeling quality, and synthetic data strategies.

• Rigorous Evaluation: Design automated objective/subjective evaluations—listening tests, SV/WER/ASR-based metrics, robustness & bias checks, and red-team studies.

• Pipeline Delivery: Harden the training → evaluation → inference pipeline; profile latency, memory, and cost; and meet production SLAs with robust monitoring and rollback.

• Safety & Responsibility: Contribute to safety/consent guardrails and to misuse/abuse mitigation for responsible speech technology.

What You’ll Bring:

• Exceptional research/development experience with large-scale audio models (>8B parameters, >500k hours of data).

• Deep hands-on experience with diffusion and/or flow-matching transformers, including practical knowledge of samplers, schedules, conditioning mechanisms, and distillation.

• Deep hands-on experience training audio VAEs, neural audio codecs, and vocoders latent/tokenizer design, reconstruction and perceptual objectives, adversarial training.

• Strong experience with multi-node, multi-GPU distributed training (FSDP/DeepSpeed or equivalent).

• Strong software engineering skills with a proven track record of building complex systems.

• Strong with PyTorch and performance work (profiling, CUDA/Triton/C++ as needed) and writing reliable production-quality code.

• Shipped large-scale speech/audio or multimodal generative models to production.

• Background in working with large-scale ML data, and the ability to iterate on data and triangulate quality using both subjective and objective signals.

• Experience with voice cloning, speech control/steerability, or expressive speech generation.

• Notable publications and/or open-source contributions in speech/audio/ML.

Compensation:

The anticipated annual base salary range for this role is between $200,000-$220,000 (€170,000-€190,000). When determining compensation, a number of factors will be considered, including skills, experience, job scope, location, and competitive compensation market data.

Benefits for U.S.-based roles:

• Competitive salary and generous company equity

• Medical, dental, and vision insurance – 99.99% of premiums covered by Cantina

• 42 days of paid time off, including:

  • 15 PTO days

  • 10 sick days

  • 15 company holidays

  • 2 floating holidays

• Generous parental leave & fertility support

• 401(k) retirement savings plan

• Lifestyle spending account – $500/month to use however you’d like

• Complimentary lunch and snacks for in-office employees

• One Medical membership, and more!