Associate Applied ML Scientist - 1087

Moscow, ID

Pay: Pay not listedSimilar roles state $165K–$240K
Work setting: On-siteLocation limits apply — work setting source
Important information before applying: Location: This position is based on-site in Moscow, Idaho, and requires five days per week in the office. We will consider only candidates who currently live locally or are willing to relocate. Work Authorization: To respect your time, we cannot provide employment visa sponsorship for this position now or in the future. Before applying, please confirm that you are authorized to work in the United States without current or future employer sponsorship.
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Employment: Full-time — employment source
Employment type Full Time
Employment type in the employer’s posting: Full Time
From the employer’s posting

Before you apply

Sponsorship: Visa sponsorship not confirmed — sponsorship source
Work Authorization: To respect your time, we cannot provide employment visa sponsorship for this position now or in the future. Before applying, please confirm that you are authorized to work in the United States without current or future employer sponsorship.
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What you’ll work on

Full posting

Develop and improve NLP models for classification, extraction, and entity linking
Train and evaluate transformer and embedding models such as BERT and Sentence Transformers
Run model evaluation, error analysis, and data analysis to find improvements
Optimize models for production on accuracy, latency, throughput, and cost
Build and maintain reproducible training and evaluation pipelines

From the employer’s posting

Develop and improve NLP models for classification, extraction, normalization, entity linking, and semantic matching.

Train and evaluate transformer-based and embedding-based models using architectures such as BERT, DeBERTa, ModernBERT, and Sentence Transformers.

Perform model evaluation, error analysis, and data analysis to identify opportunities for improvement.

Help optimize models for production with a focus on accuracy, latency, throughput, and cost.

Build and maintain reproducible training and evaluation pipelines.

What you’ll bring

All qualifications

Core experience

Bachelor’s or master’s degree in computer science, machine learning, NLP, data science, or a related field.
Experience using Python and ML frameworks such as PyTorch, Hugging Face, or scikit-learn.
Familiarity with transformers, embeddings, classification, information extraction, or entity normalization.
Experience training and evaluating machine learning models, with strong analytical and problem-solving skills.
Ability to collaborate and learn quickly in research and production environments.
Familiarity with large language models, fine-tuning, LoRA, PEFT, or prompt engineering.

Qualification wording

Bachelor’s or master’s degree in computer science, machine learning, NLP, data science, or a related field.

Experience using Python and ML frameworks such as PyTorch, Hugging Face, or scikit-learn.

Familiarity with transformers, embeddings, classification, information extraction, or entity normalization.

Experience training and evaluating machine learning models, with strong analytical and problem-solving skills.

Ability to collaborate and learn quickly in research and production environments.

Familiarity with large language models, fine-tuning, LoRA, PEFT, or prompt engineering.

Education & alternatives

Education and Experience: - Bachelor’s or master’s degree in computer science, machine learning, NLP, data science, or a related field. - Strong foundation in machine learning, natural language processing, and deep learning.

Tools in this posting

Python
AWS
Docker
MLflow
SageMaker
Hugging Face
PyTorch
scikit-learn

Source

- Strong foundation in machine learning, natural language processing, and deep learning. - Experience using Python and ML frameworks such as PyTorch, Hugging Face, or scikit-learn. - Familiarity with transformers, embeddings, classification, information extraction, or entity normalization.

- Familiarity with model optimization techniques such as quantization or distillation. - Experience with AWS, SageMaker, Docker, MLflow, or similar machine learning tools. Lightcast is a global leader in labor market insights with our headquarters located in Moscow, ID (US) and other offices in the United Kingdom, Europe, and India. We work with partners across six continents to help drive economic prosperity and mobility by providing the insights needed to build and develop our people, our institutions and companies, and our communities.

Posting record

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Actively hiringFirst seen by us 5 days ago, still listed, and not a repost of an earlier posting.

Status in our records: Live
First seen by us: Oct 24, 2026 · 5 days ago
Recorded sightings: 8
Last seen by us: Oct 30, 2026
Employer says posted: Oct 7, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

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Job description

View original posting ↗

Important information before applying:

Location: This position is based on-site in Moscow, Idaho, and requires five days per week in the office. We will consider only candidates who currently live locally or are willing to relocate.

Work Authorization: To respect your time, we cannot provide employment visa sponsorship for this position now or in the future. Before applying, please confirm that you are authorized to work in the United States without current or future employer sponsorship.

Lightcast is seeking an Associate NLP / Machine Learning Scientist to join our AI/ML Laband help develop NLP models for large-scale labor market data.You will work with senior scientists and engineers to build and improve models that transformunstructured data such as job postings and professional profiles into structured labor marketintelligence. Core problem areas include classification, information extraction, entityrecognition, normalization, semantic matching, and multilingual NLP.

Major Responsibilities:

Develop and improve NLP models for classification, extraction, normalization, entity linking, and semantic matching.

Train and evaluate transformer-based and embedding-based models using architectures such as BERT, DeBERTa, ModernBERT, and Sentence Transformers.

Support experimentation with LLMs and foundation models, including prompt-based approaches and fine-tuning techniques.

Perform model evaluation, error analysis, and data analysis to identify opportunities for improvement.

Help optimize models for production with a focus on accuracy, latency, throughput, and cost.

Build and maintain reproducible training and evaluation pipelines.

Work with multilingual labor market data and support cross-lingual model development.

Collaborate with senior scientists, ML engineers, and data engineers to productionize models.

Stay current with advances in NLP, LLMs, embeddings, and machine learning.

Education and Experience:

Bachelor’s or master’s degree in computer science, machine learning, NLP, data science, or a related field.
Strong foundation in machine learning, natural language processing, and deep learning.
Experience using Python and ML frameworks such as PyTorch, Hugging Face, or scikit-learn.
Familiarity with transformers, embeddings, classification, information extraction, or entity normalization.
Experience training and evaluating machine learning models, with strong analytical and problem-solving skills.
Ability to collaborate and learn quickly in research and production environments.
Internship, academic, or professional experience building NLP or machine learning models.
Familiarity with large language models, fine-tuning, LoRA, PEFT, or prompt engineering.
Exposure to multilingual NLP, semantic search, retrieval, or entity linking.
Familiarity with model optimization techniques such as quantization or distillation.
Experience with AWS, SageMaker, Docker, MLflow, or similar machine learning tools.

Lightcast is a global leader in labor market insights with our headquarters located in Moscow, ID (US) and other offices in the United Kingdom, Europe, and India. We work with partners across six continents to help drive economic prosperity and mobility by providing the insights needed to build and develop our people, our institutions and companies, and our communities.

Lightcast is proud to be an equal opportunity workplace and does not discriminate on the basis of federally protected statuses. Lightcast has always been, and always will be, committed to diversity of thought and unique perspectives. We seek dynamic professionals from all backgrounds to join our teams, and we encourage our employees to bring their authentic, original, and best selves to work.

Employment type

Full Time

Source details

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay: No pay amount identified in the saved description.
Location & working pattern: Moscow, ID
Important information before applying: Location: This position is based on-site in Moscow, Idaho, and requires five days per week in the office. We will consider only candidates who currently live locally or are willing to relocate. Work Authorization: To respect your time, we cannot provide employment visa sponsorship for this position now or in the future. Before applying, please confirm that you are authorized to work in the United States without current or future employer sponsorship.
Work authorization: Location: This position is based on-site in Moscow, Idaho, and requires five days per week in the office. We will consider only candidates who currently live locally or are willing to relocate. Work Authorization: To respect your time, we cannot provide employment visa sponsorship for this position now or in the future. Before applying, please confirm that you are authorized to work in the United States without current or future employer sponsorship. Lightcast is seeking an Associate NLP / Machine Learning Scientist to join our AI/ML Laband help develop NLP models for large-scale labor market data.You will work with senior scientists and engineers to build and improve models that transformunstructured data such as job postings and professional profiles into structured labor marketintelligence. Core problem areas include classification, information extraction, entityrecognition, normalization, semantic matching, and multilingual NLP.

Open source at jobs.lever.co ↗Read the full description ↓

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