Role: Principal ML with Deep Learning exp
Location: Dallas, TX OR NJ - Onsite.
Duration: 12 Months
Job Summary
We are seeking a Principal ML Systems & Alignment Engineer to lead the research, development, and deployment of advanced machine learning systems, with a focus on AI alignment, model behavior, safety, and reliability. The ideal candidate will have deep research expertise in ML/Deep Learning and hands-on experience building, evaluating, and aligning large-scale AI models.
Key Responsibilities
- Lead research and development of advanced ML and deep learning systems.
- Design and implement AI alignment techniques to improve model behavior, reliability, and safety.
- Work on LLM training, fine-tuning, optimization, and evaluation.
- Apply techniques such as Reinforcement Learning from Human Feedback (RLHF), Direct Preference Optimization (DPO), and preference modeling.
- Develop model evaluation frameworks, benchmarks, and safety testing methodologies.
- Investigate model robustness, hallucinations, bias, interpretability, and failure modes.
- Optimize large-scale ML training and inference systems.
- Collaborate with research scientists, ML engineers, and cross-functional teams.
- Provide technical leadership and mentor engineering and research teams.
Required Skills
- PhD in Deep Learning, Machine Learning, AI, or a related field – Mandatory.
- Strong research background in machine learning, deep learning, and neural networks.
- Expertise in LLMs, Transformer architectures, and generative AI.
- Experience with AI alignment, RLHF, DPO, reward modeling, or preference optimization.
- Strong programming skills in Python and frameworks such as PyTorch or TensorFlow.
- Experience with model training, fine-tuning, evaluation, and optimization.
- Knowledge of AI safety, model robustness, interpretability, and responsible AI.
- Experience with distributed training and large-scale ML systems is preferred.
- Strong research publication record in relevant AI/ML conferences or journals is a plus.
Preferred Qualifications
- Experience working on frontier AI models or advanced LLM research.
- Publications in NeurIPS, ICML, ICLR, ACL, or similar conferences.
- Experience with large-scale GPU infrastructure and distributed computing.
- Experience developing alignment and safety evaluation frameworks.
Ideal Candidate
A research-oriented ML/AI expert with a mandatory PhD, strong hands-on deep learning experience, and proven expertise in LLM alignment, model evaluation, and large-scale ML systems.
Thanks and Regards,
Pooja Jaiswal – Technical Recruiter
Aptino, Inc.