IAlchemy Inc.
Requirements · BS/MS/PhD in Computer Science, Machine Learning, AI, Applied Mathematics, or a related quantitative technical field (MS/PhD preferred) · 2-3 years of relevant industry or research engineering experience in ML/AI systems · Hands-on experience with LLM training / fine-tuning / post-training, including at least one of: o supervised fine-tuning (SFT) o preference optimization (e.g., DPO or related methods) o RLHF / RLAIF-style workflows o task- or domain-adaptation of foundation models · Strong programming skills in Python and experience building production-quality ML code · Experience with modern ML frameworks (e.g., PyTorch, JAX, TensorFlow) and model libraries/tooling (e.g., Hugging Face ecosystem, vLLM, distributed training stacks) · Experience designing and implementing evaluation pipelines for LLM/ML systems , including metrics computation, dataset handling, and experiment comparisons · Strong understanding of data pipelines and ML systems engineering, including reproducibility, observability, and debugging · Experience with large-scale distributed ML systems and performance optimization for training/evaluation workloads (GPU/accelerator environments preferred) · Experience with large-scale data processing and workflow orchestration in support of model training/evaluation · Ability to collaborate directly with technical stakeholders including research scientists, ML engineers, data engineers, and customer technical leads · Strong written and verbal communication skills, including the ability to explain complex technical tradeoffs to both technical and non-technical audiences Technical skills ML / LLM Engineering · Experience training, fine-tuning, and evaluating transformer-based models · Understanding of post-training workflows and model iteration loops · Familiarity with inference-time considerations (latency, throughput, memory/performance tradeoffs) where relevant to evaluation or deployment Evaluation & Experimentation · Experience implementing automated evaluation pipelines and test harnesses · Experience with experiment tracking, versioning, and reproducibility practices · Ability to assess metric quality and ensure consistency across model comparisons Software / Data Engineering · Proficiency in Python and strong software engineering fundamentals · Experience with data processing pipelines, storage formats, and scalable dataset workflows · Familiarity with CI/CD, testing, and engineering quality practices for ML systems Preferred Skills · Experience with multimodal model training/evaluation (text + image/audio/video) · Experience with long-context evaluation and/or model adaptation for long-context tasks · Experience with agentic or multi-turn evaluation harnesses, tool-use simulation, or interactive environment testing · Experience working in customer-facing technical consulting, solutions engineering, or applied research delivery · Familiarity with LLM safety, alignment, robustness, or red-teaming evaluation approaches · Contributions to open-source ML/LLM tooling or published technical work in relevant areas Application Question(s): Open to work in a night shift schedule Education: Bachelor's (Preferred) Experience: multimodal model training/evaluation : 3 years (Preferred) AI/ML Research Engineer: 3 years (Preferred) Work Location: Remote
IAlchemy Inc.
