Natural language annotator Job at One Forma

Mint

Participants will be requested to review and annotate bilingual text across the ...

Location

Salary:

Not provided

One Forma

Expiration Date

Until further notice

Requirements

Being a native speaker/highly proficient in both source and target languages

Job Responsibility

Review and annotate bilingual text across the language pair assigned, evaluating both source and target text quality
Evaluate the source text itself for naturalness and language correctness
Annotations will be done following an annotation schema provided by our client
Tasks will be done on our online platform
Review AI-generated translations for accuracy, fluency, and idiomatic usage
Ensure translations follow the grammar and syntax rules of the target language

New

Lead Applied Scientist Security Models Training Team

The Security Models Training team is expanding to drive the development of a new...

Location

Israel , Tel Aviv, Herzliya

Salary:

Not provided

Microsoft Corporation

Expiration Date

Until further notice

Requirements

M.Sc. / Ph.D. in Computer Science, Information Systems, Electrical or Computer Engineering or Data Science (Ph.D. strongly preferred)
Candidates with M.Sc. / Ph.D. in related fields with proven industry experience or a strong publication record in the areas of LLM, Information Retrieval, Machine Learning, Natural Language Processing, Time Series Forecasting and Deep Learning are considered as well
Proven hands-on experience of at least 8 years (including post-grad work) in building and deploying Machine Learning products
Key areas of expertise include Natural Language Processing and Large Language Models, along with an understanding of concepts such as Privacy and Responsible AI
Candidates are expected to demonstrate a strong history of successfully translating applied research into production-ready solutions, along with a proven track record of delivering projects within large-scale production environments
Demonstrated ability to set long‑term technical strategy, align multiple teams, and serve as a technical decision‑maker for high‑risk, high‑impact investments
Proven expertise in the LLM and/or time-series forecasting domain, demonstrating comprehensive knowledge of relevant concepts in the domain
Ideal applicants should be proficient in areas such as LLM’s pre and post training, including CPT, SFT and RL, LLM benchmarking, agentic flows, and model alignment
Hands-on experience in building neural model architectures at the 100M+ scale and the proficiency to adapt them at all abstraction levels down the individual block (e.g. changing the innerworkings of an attention block, introducing new blocks, or changing the routings)
Demonstrated proficiency in problem-solving and data analysis, with substantial expertise in evaluating the performance of large language models (LLMs) and/or time-series forecasting models, developing benchmarks tailored to practical scenarios

Job Responsibility

Technical Leadership & Ownership: set technical direction for major security domain initiatives and align roadmaps across multiple teams
lead security model programs spanning pre‑training, task tuning, reinforcement learning, and evaluation
translate cutting‑edge research into production‑ready capabilities
This role influences portfolio‑level technical tradeoffs, investment prioritization, and long‑term architecture decisions for security models
Advanced Model Design – Building and customizing deep learning model architectures (e.g., modifying transformer blocks, attention/memory modules, etc.) at the SLM/LLM scale
making principled architectural tradeoffs to improve reliability, robustness, and security‑specific behavior
Advanced Model Training – Apply deep expertise in pre-training, post-training, and reinforcement learning (RL) for both language and other modalities, including time-series
Design & Evaluate Datasets – Build high-quality datasets and benchmarks
define objective evaluation frameworks and quality gates
run ablation studies to measure impact and optimize data and training effectiveness to support confident product decisions

Fulltime

AI/ML & Data Engineer

Location

India , Chennai

Salary:

Not provided

Congruent

Expiration Date

Until further notice

Requirements

4~6 years in ML/NLP, preferably in document-heavy domains (finance, legal, policy)
Languages: Python, SQL
AI/ML/NLP: Hugging face transformers, OpenAI API, Spacy, Scikit-Learn, LangChain, RAG, LLM prompt-tuning, LLM fine-tuning
Vector Search: Pinecone, Weaviate, FAISS
Data Engineering: Airflow, Kafka, OCR (Tesseract, pdfminer)
MLOps: MLflow, Docker

Job Responsibility

Data Ingestion and Preprocessing: Ability to build and maintain data pipelines to ingest unstructured data from PDFs, gazettes, HTML circulars etc. and process data extraction, parsing, and normalization
NLP & LLM Modeling: Ability to fine-tune or prompt-tune LLMs for summarization, classification, and change detection in regulations. Ability to develop embeddings for semantic similarity.
Knowledge Graph Engineering: Ability to design entity relationships (regulation, control, policy) and implement retrieval over Neo4j or similar graph DBs.
Information Retrieval (RAG): Ability to build RAG pipelines for natural language querying of regulations.
Annotation and Validation: Ability to annotate training data by collaborating with SMEs and validate model outputs
MLOps: Ability to build CI/CD for model retraining, versioning, and evaluation (precision, recall, BLEU, etc.)
API and Integration: Ability to expose ML models as REST APIs (FastAPI) for integration with product frontend.

New

Principal/Senior Applied Scientist Security Models Training Team - Next-Gen frontier research

The Security Models Training team is expanding to drive the development of a new...

Location

Israel , Tel Aviv, Herzliya

Salary:

Not provided

Microsoft Corporation

Expiration Date

Until further notice

Requirements

M.Sc. / Ph.D. in Computer Science, Information Systems, Electrical or Computer Engineering or Data Science (Ph.D. strongly preferred)
Candidates with M.Sc. / Ph.D. in related fields with proven industry experience or a strong publication record in the areas of LLM, Information Retrieval, Machine Learning, Natural Language Processing, Time Series Forecasting and Deep Learning are considered as well
Proven hands-on experience of at least 5 years (including post-grad work) in building and deploying Machine Learning products
Key areas of expertise include Natural Language Processing and Large Language Models, along with an understanding of concepts such as Privacy and Responsible AI
Candidates are expected to demonstrate a strong history of successfully translating applied research into production-ready solutions, along with a proven track record of delivering projects within large-scale production environments
Proven expertise in the LLM and/or time-series forecasting domain, demonstrating comprehensive knowledge of relevant concepts in the domain
Ideal applicants should be proficient in areas such as LLM’s pre and post training, including CPT, SFT and RL, LLM benchmarking, agentic flows, and model alignment
Hands-on experience in building neural model architectures at the 100M+ scale and the proficiency to adapt them at all abstraction levels down the individual block (e.g. changing the innerworkings of an attention block, introducing new blocks, or changing the routings)
Demonstrated proficiency in problem-solving and data analysis, with substantial expertise in evaluating the performance of large language models (LLMs) and/or time-series forecasting models, developing benchmarks tailored to practical scenarios

Job Responsibility

Technical Leadership & Ownership: set technical direction for major security domain initiatives
lead security model programs spanning pre‑training, task tuning, reinforcement learning, and evaluation
translate cutting‑edge research into production‑ready capabilities
Advanced Model Design – Building and customizing deep learning model architectures (e.g., modifying transformer blocks, attention/memory modules, etc.) at the SLM/LLM scale
making principled architectural tradeoffs to improve reliability, robustness, and security‑specific behavior
Advanced Model Training – Apply deep expertise in pre-training, post-training, and reinforcement learning (RL) for both language and other modalities, including time-series
Design & Evaluate Datasets – Build high-quality datasets and benchmarks
define objective evaluation frameworks and quality gates
run ablation studies to measure impact and optimize data and training effectiveness to support confident product decisions
Develop Data Infrastructure – Create and maintain scalable pipelines for ingestion, preprocessing, filtering, and annotation of large, complex datasets, with attention to privacy, governance, and long‑term reuse across security scenarios

Fulltime

Japanese audio collection projects

The Voice Command Audio Collection Project focuses on collecting natural speech ...

Location

Japan , Tokyo

Salary:

Not provided

Sigma AI

Expiration Date

Until further notice

Requirements

Fluent in the language you are applying for
Knowledge of English is optional
Mobile phone with Android OS
Minimum 4GB RAM
Microphone and webcam
Operating system: Windows 10 or higher, macOS 13 Ventura or higher
All OS updates installed and supported by the vendor
Stable internet connection
Headphones
Secure internet location, protected by a strong password

Job Responsibility

Produce a total of 500 short utterances, completed across two recording sessions
Deliver recordings in a natural, conversational tone, with expressive and realistic intonation to reflect everyday voice interactions

Italian audio collection projects

The Voice Command Audio Collection Project focuses on collecting natural speech ...

Location

Italy

Salary:

Not provided

Sigma AI

Expiration Date

Until further notice

Requirements

Fluent in the language you are applying for
Knowledge of English is optional
Mobile phone with Android OS (Tablets and iOS devices are not supported)
Minimum 4GB RAM
Microphone and webcam
Operating system: Windows 10 or higher or macOS 13 Ventura or higher
All OS updates installed and supported by the vendor
Stable internet connection
Headphones
Secure internet location, protected by a strong password

Job Responsibility

Produce a total of 500 short utterances, completed across two recording sessions
Deliver recordings in a natural, conversational tone, with expressive and realistic intonation to reflect everyday voice interactions

AI/ML Engineer (IoT sphere)

This AI-driven initiative focuses on improving the client's smart video ecosyste...

Location

Salary:

Not provided

Coherent Solutions

Expiration Date

Until further notice

Requirements

5+ years of experience in ML/AI engineering
Strong proficiency in Python and experience with ML frameworks such as TensorFlow and PyTorch
Proficient in building distributed workflows using Apache Spark or Databricks
Hands-on experience in cloud environments (AWS and/or Azure)
Familiarity with FastAPI, Docker, and CI/CD practices
Background in computer vision, including object detection and tracking (YOLO, SAM, SSD)
Experience working with annotation tools (Label Studio, CVAT, etc.) and dataset management
Understanding of LLMs, transformers, and generative AI techniques
experience with LangChain or similar orchestration frameworks
Proficiency in building scalable, fault-tolerant ML pipelines with monitoring/logging

Job Responsibility

Design, develop, and validate smart video search and summarization systems
Build and optimize ML pipelines for object detection, event tagging, and descriptive alerts
Collaborate with firmware teams to implement automated model testing on target devices
Work with video datasets to curate, label, and annotate events for AI training
Integrate LLMs to contextualize visual events and enable semantic grouping
Maintain high-quality production-grade code for APIs and ML services
Partner with product and engineering teams to ship AI-driven features for intelligent notifications
Implement monitoring, observability, and continuous evaluation for deployed models

What we offer

Technical and non-technical training for professional and personal growth
Internal conferences and meetups to learn from industry experts
Support and mentorship from an experienced employee to help you professional grow and development
Internal startup incubator
Health insurance
English courses
Sports activities to promote a healthy lifestyle
Flexible work options, including remote and hybrid opportunities
Referral program for bringing in new talent
Work anniversary program and additional vacation days

Senior Research Scientist

PolyAI automates customer service through lifelike voice assistants that let cus...

Location

United Kingdom , London

Salary:

Not provided

PolyAI

Expiration Date

Until further notice

Requirements

PhD in Machine Learning, Natural Language Processing, Computer Science, or a related field
5+ years of hands-on experience in deep learning
Proven track record of research innovation, including published work or deployed systems
Strong programming skills in Python and deep learning frameworks like PyTorch
Demonstrated expertise in at least one domain area such as reinforcement learning, conversational AI, audio modelling, or LLM alignment
Experience leading projects end-to-end, from ideation to deployment
Excellent communication skills with the ability to write clear technical documents and explain complex concepts to diverse audiences
Comfortable working in ambiguity and driving clarity through experimentation and data

Job Responsibility

Lead and execute complex research projects with clear business impact
Design and implement novel post-training strategies including preference tuning, reward modeling, and synthetic supervision
Develop innovative model architectures and training approaches for conversational AI, including speech-aware and multimodal models
Conduct empirical studies to assess model performance in live deployments and iterate quickly based on real-world data
Generate, collect, and annotate training data - including synthetic and real-world conversational datasets - with an eye for quality and bias mitigation
Design robust evaluation metrics and benchmarks for LLM-based assistants in customer service domains
Work closely with engineering and product teams to integrate research into production environments
Collaborate with legal and compliance teams to ensure responsible use of data and models
Stay current with academic and industry advances in LLMs, ASR, TTS, RLHF, and multimodal learning

What we offer

Participation in the company’s employee share options plan
Tenure-Based PTO: You will receive 25 holidays when you join and will gain an additional 1 day after 2 years of service, then 1 day each year until capped at 32 holidays
Flexible working from home policy
Work from outside of the UK for up to 6 months each year
TELUS Health EAP 24/7 - offers you and your chosen family confidential, judgment-free support for any work, health, or life challenge
Enhanced parental leave
Bike2Work scheme
Annual learning and development allowance
We’re all about making WFH work for you - that’s why we offer a one-off WFH allowance when you join. Offering perks like noise-cancelling headphones or a comfortable desk chair to boost your comfort and focus!
Company-funded fertility and family-forming programmes

Natural language annotator

One Forma

Location:

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Additional Information:

Job Posted:
February 16, 2026

Looking for more opportunities? Search for other job offers that match your skills and interests.

Similar Jobs for Natural language annotator

Mint