Training Pipelines jobs

Research Scientist, Post-Training

True Talent Solutions Partners · Posted Nov 13, 2026

Open

San Francisco, California, United States
On-site
Full-time · Entry
$150K–$250K per year
0–4 years

Research Scientist, Post-Training

True Talent Solutions Partners · Posted Nov 13, 2026

Open

San Francisco, California, United States
On-site
Full-time · Entry
$150K–$250K per year
0–4 years

Senior AI Engineer

UFORCE · Posted Nov 12, 2026

Open

London, England, United Kingdom
Full-time · Senior
5+ years

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Build the end-to-end system that lets customers adapt UFORCE models on their own private data without exposing that data to us, spanning data processing, foundation-model-assisted labeling, human-in-the-loop QA, active learning, training, evaluation, and model promotion.

Responsibilities

Own the ML adaptation pipeline from raw customer data to trained, evaluated, deployable models.
Build foundation-model-assisted labeling workflows using tools such as SAM-2, Grounding DINO, open-vocabulary models, LLM steering, and human review.
Design self-serve operator workflows using yes/no/maybe feedback and natural-language corrections.
Create versioned datasets with lineage, data cards, label provenance, class distributions, and known gaps.
Build QA methods that catch systematic pseudo-label errors, missing annotations, and long-tail data gaps.

Requirements

Nice to have: Synthetic data
Nice to have: Sim2real
Nice to have: Domain randomization
Nice to have: EO/IR
Nice to have: LWIR

Skills

Python PyTorch ML data pipelines Training pipelines

Senior Machine Learning Engineer

ExaCare AI · Posted Apr 14, 2026

Open

New York, New York, United States
Hybrid
Senior

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Senior Machine Learning Engineer, MLOps to operationalize and scale machine learning systems.

Compensation

Competitive salary and equity in a high-growth startup

Responsibilities

Build and maintain the workflows and infrastructure that support the end-to-end ML lifecycle
Partner with researchers and ML practitioners to productionize models and enable faster iteration
Design, build, and improve data pipelines and training pipelines
Improve data processing, annotation workflows, and ML system efficiency
Deploy and maintain the background systems that support model training and inference

Skills

Machine Learning Engineering MLOps Data Engineering Training Pipelines Deployment Workflows Monitoring Systems Production Systems Software Engineering Fundamentals

Senior Staff AI Systems Engineer

Northrop Grumman · Posted Nov 11, 2026

Open

Linthicum, Maryland, United States
On-site
Full-time · Senior
$223K–$334K per year
10+ years

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Compensation

Primary Level Salary Range: $222,700.00 - $334,100.00

Responsibilities

Senior consultant for AI/ML target identification and classification for onboard real-time environments.
Design and implement algorithms using machine learning and sensor fusion for multi-modal target recognition.
Define data strategies including collection, labeling, simulation, synthetic data generation, domain adaptation, and data quality governance.
Develop training and evaluation pipelines with rigorous performance metrics.
Architect resilient real-time embedded solutions to execute within existing software architecture.

Requirements

Bachelor's Degree
Master's Degree
PhD
Nice to have: SAR processing
Nice to have: GMTI/SMTI

Skills

machine learning algorithms sensor fusion data strategies training pipelines embedded solutions

Senior Research Engineer, Generative 3D

MimoLabs · Posted Oct 28, 2026

Open

Remote, United States
Remote
Full-time · Senior
$170K–$220K per year

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Build and train generative 3D models and training pipelines, lead research practice, and bring models to production.

Compensation

$170K–$220K base and equity, four-year vesting with a one-year cliff.

Responsibilities

Build and train models that turn intent into manufacturable geometry
Put physics in the loop with differentiable simulation and physics-driven optimization
Own the training pipeline end to end
Build understanding side: part segmentation, semantic classification and spatial comprehension of CAD and mesh data
Run the research practice: read the field, reproduce methods, write go/no-go memos

Requirements

Nice to have: Topology optimization
Nice to have: Computational design
Nice to have: GPU serving
Nice to have: Contact modeling
Nice to have: Material models

Skills

Generative 3D diffusion Flow models Implicit representations Voxel representations Latent-space optimization

Machine Learning Engineer

Coframe · Posted Nov 10, 2026

Open

San Francisco, California, United States +1 more
On-site

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Build and own machine learning models that power performance optimization at Coframe, from research and training to production deployment.

Locations (2)

San Francisco, California, United States
San Francisco Bay Area, United States

Responsibilities

Build foundation models and customer‑specific models for performance optimization
Fine‑tune VLMs and LLMs to understand and improve digital experiences
Train ranking, CTR, conversion, and engagement models that guide what Coframe generates and ships
Own the full model lifecycle, from idea and research through training, evaluation, and deployment
Build and scale the ML infrastructure for training, serving, and monitoring models in production

Skills

fine‑tuning vision‑language models fine‑tuning large language models

ML Engineer

Xperteez Technology · Posted Nov 9, 2026

Open

Remote
Remote
Contract · Senior
$60–$120 per hour

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Senior ML Engineer (MSc. or PhD) contributing to AI training projects involving model development, training and inference systems, numerical computing, performance optimization, and Python.

Compensation

Pay: $60–$120/hour

Responsibilities

Develop and validate machine-learning models, training pipelines, inference systems, and supporting infrastructure.
Implement model components, data pipelines, evaluation systems, and numerical methods.
Build reproducible programmatic workflows using Python and command-line tools.

Requirements

Master’s degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a closely related quantitative discipline.

Skills

Python coding agents machine learning model development training pipelines inference systems

Research Scientist, Post-Training

Research Scientist, Post-Training

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Senior AI Engineer

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Senior Machine Learning Engineer

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Senior Staff AI Systems Engineer

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Senior Research Engineer, Generative 3D

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Requirements

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Machine Learning Engineer

Locations (2)

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ML Engineer

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