Principal Machine Learning Engineer, Artificial Intelligence – AI

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🏄 California – Remote

🏄 California – Remote

💵 $170k - $200k / year

⏰ Full Time

🔴 Lead

🤖 AI Engineer

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TTEC

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1984

🤝 B2B

💰 Post-IPO Debt on 2021-11

B2B • Customer Experience • AI

TTEC is a global customer experience technology and services company that specializes in Customer Experience (CX) strategy, contact center operations, and AI-enhanced services. Serving brands across diverse industries, TTEC employs a unique blend of human talent and AI technology to optimize customer interactions and drive satisfaction. With over 54,000 employees across 80+ contact centers, TTEC provides tailored solutions that enhance customer journeys, improve operational efficiency, and foster long-term loyalty.

📋 Description

• Architect and build large-scale ML systems spanning data, training, evaluation, inference, and deployment. • Design reproducible, high-performance training pipelines across GPU infrastructure. • Architect inference systems that balance latency, throughput, cost, and reliability at scale. • Design and maintain data systems for high-quality synthetic and real-world training data. • Implement evaluation pipelines covering performance, robustness, safety, and bias, in partnership with research leadership. • Own production deployment, including GPU optimization, memory efficiency, latency reduction, and scaling policies. • Collaborate closely with application engineering to integrate ML systems cleanly into backend, mobile, and desktop products. • Make pragmatic trade-offs and ship improvements quickly, learning from real usage. • Work under real production constraints: latency, cost, reliability, and safety

🎯 Requirements

• Strong background in deep learning and transformer-based architectures. • Artificial Intelligence (AI) experience required. • Hands-on experience training, fine-tuning, or deploying large-scale ML models in production. • Proficiency with at least one modern ML framework (e.g. PyTorch, JAX), and ability to learn others quickly. • Experience with distributed training and inference frameworks (e.g. DeepSpeed, FSDP, Megatron, ZeRO, Ray). • Strong software engineering fundamentals; you write robust, maintainable, production-grade systems. • Experience with GPU optimization, including memory efficiency, quantization, and mixed precision. • Comfort owning ambiguous, zero-to-one ML systems end-to-end. • A bias toward shipping, learning fast, and improving systems through iteration. • Experience with LLM inference frameworks such as vLLM, TensorRT-LLM, or FasterTransformer. • Contributions to open-source ML or systems libraries. • Background in scientific computing, compilers, or GPU kernels. • Experience with RLHF pipelines (PPO, DPO, ORPO). • Experience training or deploying multimodal or diffusion models. • Experience with large-scale data processing (Apache Arrow, Spark, Ray).

🏖️ Benefits

• medical insurance • Dental • Vision • Savings Plan Options • PTO