AI/ML Fine-Tuning and Training Engineer

Verterim, Inc.

AI/ML Fine-Tuning and Training Engineer at Verterim focused on designing, training, and evaluating models for AI products. Collaborating with the CTO and AI Solutions Engineering team to optimize machine learning solutions.

Posted 7/11/2026full-timeRemote • 🇮🇳 IndiaMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

PythonPyTorch

About the role

Key responsibilities & impact

Fine-tune and train large language models and other ML models as directed by Verterim's CTO, translating technical strategy into trained, deployable model artifacts.
Design and execute fine-tuning pipelines (full fine-tuning, LoRA/QLoRA, instruction tuning, RLHF/DPO) tailored to GRC, risk, compliance, and audit use cases.
Curate, clean, and structure training and evaluation datasets, including synthetic data generation and domain-specific labeling workflows.
Optimize model performance across accuracy, latency, cost, and resource utilization for production deployment.
Build and maintain rigorous evaluation harnesses, benchmarks, and regression suites to validate model quality prior to release.
Ensure fine-tuned models meet enterprise expectations for accuracy, explainability, traceability, and defensibility in regulated environments.
Detect and mitigate bias, hallucination, and drift through structured testing and continuous monitoring.
Document model lineage, training data provenance, hyperparameters, and evaluation results to support audit and governance requirements.
Manage end-to-end training infrastructure and workflows, including compute provisioning, experiment tracking, and versioning of models and datasets.
Partner with AI Solutions Engineering to integrate trained models into RAG pipelines, agent orchestration frameworks, and knowledge-base systems.
Establish reproducible, automated pipelines for retraining, fine-tuning refreshes, and model promotion from experimentation to production.
Maintain technical documentation, training runbooks, and internal enablement artifacts for models in production.
Serve as the primary technical point of contact for model training and fine-tuning matters between the CTO, engineering, and product teams.
Ensure model development aligns with Verterim's internal AI governance model, quality funnel standards, and responsible AI principles.
Partner with the CTO and Product Management to translate business, regulatory, and customer requirements into model training objectives.
Support customer-facing technical discussions where deep model architecture or performance detail is required.

Requirements

What you’ll need

4+ years of experience in machine learning engineering, applied NLP, or LLM training/fine-tuning roles.
Demonstrated hands-on experience fine-tuning large language models (e.g., LoRA/QLoRA, full fine-tuning, instruction tuning, or RLHF/DPO).
Strong proficiency in Python and modern ML frameworks (PyTorch, Hugging Face Transformers/PEFT/TRL, or equivalent).
Solid understanding of model evaluation methodology, including benchmark design, offline/online evaluation, and regression testing.
Proven ability to execute under strong technical leadership while translating strategy into working, production-ready models.
Strong communication skills with the ability to operate effectively with executive-level technical leadership.

Benefits

Comp & perks

Minimal travel required for technical reviews and select industry/conference events

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

Fine-Tuning PipelinesSynthetic Data GenerationModel Performance OptimizationBias Detection and MitigationModel DocumentationExperiment TrackingVersioning of ModelsAutomated PipelinesRegulatory ComplianceRisk and Compliance Use Cases

Soft Skills

Strong Communication SkillsCollaboration with Executive Leadership