Senior Data Scientist / ML Engineer Job at Intellias

Senior Speech & Audio Biomarkers ML Engineer / Data Scientist / LLM Researcher

Adalyon is transforming clinical trials with a behavioural-intelligence platform...

Location

Finland

Salary:

Not provided

Life Science Talent

Expiration Date

Until further notice

Requirements

Advanced degree PhD, postdoctoral experience, or equivalent research depth in speech technology, audio signal processing, acoustics, machine learning, data science, computational linguistics, or a related field
Audio and NLP experience – You have built systems that process raw audio and transcripts to derive actionable insights. Familiarity with prosodic and spectral features, and the ability to engineer features like jitter, shimmer and harmonic-to-noise ratio, which have been shown to correlate with cognitive and emotional conditions
Speech processing toolkits: Experience with speech processing toolkits (e.g., librosa, Kaldi, Praat) and ML frameworks (PyTorch, TensorFlow, scikit-learn) is essential
LLM expertise – Hands-on experience with large language models, including prompting, fine-tuning and integrating them into downstream ML pipelines. Ability to interpret and control LLM outputs to ensure transparency and reproducibility, avoiding the unpredictable behaviour of generic LLMs
Startup mindset – Comfortable working in an agile, evolving environment. You take initiative, think creatively and can operate with limited structure. You thrive when delivering an MVP while planning for scalable solutions
Practical programming ability, ideally in Python and relevant scientific/data tooling. You do not need to be a software engineer, but you must be able to build the systems and pipelines needed for your research.

Job Responsibility

Conversational design & data pipeline
Signal processing & feature extraction
Model development & integration
Validation & evidence generation
Research & innovation

What we offer

A competitive salary package that reflects your experience and the value you create
The opportunity to work with advanced AI, acoustic analysis, and speech-based biomarker technology at an early stage
A central and highly influential role with direct access to research and technology leadership
High autonomy, high visibility, and the opportunity to shape the scientific foundation of a growing company
A dynamic and flexible startup environment with room for deep technical discussion, scientific exploration, and practical impact

Fulltime

Senior Data Scientist (ML Engineering)

As CLEAR continues to scale, we’re deepening our investment in the data science ...

Location

United States , New York

Salary:

175000.00 - 215000.00 USD / Year

Clear

Expiration Date

Until further notice

Requirements

6+ years of experience in data science, machine learning, or applied statistics within a modern cloud data environment like AWS Sagemaker
Expert-level Python with deep experience in scientific libraries (e.g. pandas, NumPy, SciPy, matplotlib), machine learning frameworks (e.g. scikit-learn, XGBoost, LightGBM, pytorch), and model evaluation tooling
Strong SQL skills and experience working with cloud data warehouses (e.g. Snowflake, BigQuery, Redshift)
Experience with modern ML workflow tools (e.g., Airflow, Dagster, MLflow, Vertex / SageMaker, Voxel 51)
Deep understanding of statistical methods, experiment design, data cleansing, feature engineering, and model interpretability
Proven ability to turn ambiguous business problems into measurable modeling approaches—balancing analytical rigor with practical business impact
Experience deploying production models and maintaining them through their lifecycle (monitoring, retraining, performance management)
Strong communication, stakeholder influence, and storytelling skills
you can translate complex data science work into insights and decisions
A proactive, curious mindset with a passion for standardization, repeatability, and scaling high-quality modeling practices

Job Responsibility

Own and evolve CLEAR’s predictive modeling ecosystem: design, train, and optimize statistical and machine learning models for our digital identity platform that support product, risk, fraud, operations, and member experience teams
Develop high-quality production code including feature engineering pipelines, model training workflows, and evaluation frameworks that meet reliability and performance standards
Partner with Data Engineering and ML Platform teams to deploy models into production, define scalable data pipelines, and ensure real-time and batch inference systems run efficiently
Advance CLEAR’s AI & ML capabilities by designing reusable modeling components, improving model documentation, and contributing to a roadmap for integrating ML into core products and decision flows
Improve experimentation and insight generation by building robust tooling and analytical frameworks, designing statistical tests, and synthesizing results into clear and actionable recommendations for cross-functional teams
Mentor analysts, data scientists, and ML engineers, guiding them on Python best practices, model development, data exploration, and communicating insights effectively

What we offer

comprehensive healthcare plans
family-building benefits (fertility and adoption/surrogacy support)
flexible time off
annual wellness stipend
free OneMedical memberships for you and your dependents
a CLEAR Plus membership
a 401(k) retirement plan with employer match
catered lunches every day
fully stocked kitchens
stipends and reimbursement programs for well-being and learning & development

Fulltime

Senior ML Data Engineer

As a Senior Data Engineer, you will play a pivotal role in our AI/ML workstream,...

Location

Poland , Warsaw

Salary:

Not provided

Awin Global

Expiration Date

Until further notice

Requirements

Bachelor or Master’s degree in data science, data engineering, Computer Science with focus on math and statistics / Master’s degree is preferred
At least 5 years experience as AI/ML data engineer undertaking above task and accountabilities
Strong foundation in computer science principes and statistical methods
Strong experience with cloud technology (AWS or Azure)
Strong experience with creation of data ingestion pipeline and ET process
Strong knowledge of big data tool such as Spark, Databricks and Python
Strong understanding of common machine learning techniques and frameworks (e.g. mlflow)
Strong knowledge of Natural language processing (NPL) concepts
Strong knowledge of scrum practices and agile mindset
Strong Analytical and Problem-Solving Skills with attention to data quality and accuracy

Job Responsibility

Design and maintain scalable data pipelines and storage systems for both agentic and traditional ML workloads
Productionise LLM- and agent-based workflows, ensuring reliability, observability, and performance
Build and maintain feature stores, vector/embedding stores, and core data assets for ML
Develop and manage end-to-end traditional ML pipelines: data prep, training, validation, deployment, and monitoring
Implement data quality checks, drift detection, and automated retraining processes
Optimise cost, latency, and performance across all AI/ML infrastructure
Collaborate with data scientists and engineers to deliver production-ready ML and AI systems
Ensure AI/ML systems meet governance, security, and compliance requirements
Mentor teams and drive innovation across both agentic and classical ML engineering practices
Participate in team meetings and contribute to project planning and strategy discussions

What we offer

Flexi-Week and Work-Life Balance: We prioritise your mental health and well-being, offering you a flexible four-day Flexi-Week at full pay and with no reduction to your annual holiday allowance. We also offer a variety of different paid special leaves as well as volunteer days
Remote Working Allowance: You will receive a monthly allowance to cover part of your running costs. In addition, we will support you in setting up your remote workspace appropriately
Pension: Awin offers access to an additional pension insurance to all employees in Germany
Flexi-Office: We offer an international culture and flexibility through our Flexi-Office and hybrid/remote work possibilities to work across Awin regions
Development: We’ve built our extensive training suite Awin Academy to cover a wide range of skills that nurture you professionally and personally, with trainings conveniently packaged together to support your overall development
Appreciation: Thank and reward colleagues by sending them a voucher through our peer-to-peer program

Senior ML Data Engineer

As a Senior Data Engineer, you will play a pivotal role in our AI/ML workstream,...

Location

Salary:

Not provided

Awin Global

Expiration Date

Until further notice

Requirements

Bachelor or Master’s degree in data science, data engineering, Computer Science with focus on math and statistics / Master’s degree is preferred
At least 5 years experience as AI/ML data engineer undertaking above task and accountabilities
Strong foundation in computer science principes and statistical methods
Strong experience with cloud technology (AWS or Azure)
Strong experience with creation of data ingestion pipeline and ET process
Strong knowledge of big data tool such as Spark, Databricks and Python
Strong understanding of common machine learning techniques and frameworks (e.g. mlflow)
Strong knowledge of Natural language processing (NPL) concepts
Strong knowledge of scrum practices and agile mindset

Job Responsibility

Design and maintain scalable data pipelines and storage systems for both agentic and traditional ML workloads
Productionise LLM- and agent-based workflows, ensuring reliability, observability, and performance
Build and maintain feature stores, vector/embedding stores, and core data assets for ML
Develop and manage end-to-end traditional ML pipelines: data prep, training, validation, deployment, and monitoring
Implement data quality checks, drift detection, and automated retraining processes
Optimise cost, latency, and performance across all AI/ML infrastructure
Collaborate with data scientists and engineers to deliver production-ready ML and AI systems
Ensure AI/ML systems meet governance, security, and compliance requirements
Mentor teams and drive innovation across both agentic and classical ML engineering practices
Participate in team meetings and contribute to project planning and strategy discussions

What we offer

Flexi-Week and Work-Life Balance: We prioritise your mental health and well-being, offering you a flexible four-day Flexi-Week at full pay and with no reduction to your annual holiday allowance. We also offer a variety of different paid special leaves as well as volunteer days
Remote Working Allowance: You will receive a monthly allowance to cover part of your running costs. In addition, we will support you in setting up your remote workspace appropriately
Pension: Awin offers access to an additional pension insurance to all employees in Germany
Flexi-Office: We offer an international culture and flexibility through our Flexi-Office and hybrid/remote work possibilities to work across Awin regions
Development: We’ve built our extensive training suite Awin Academy to cover a wide range of skills that nurture you professionally and personally, with trainings conveniently packaged together to support your overall development
Appreciation: Thank and reward colleagues by sending them a voucher through our peer-to-peer program

Senior Staff Data Engineer- ML & AI Platform

At Marktplaats, data is at the heart of everything we do, but Intelligence is wh...

Location

Netherlands , Amsterdam

Salary:

Not provided

Adevinta

Expiration Date

Until further notice

Requirements

10+ years of experience with a specific focus on the intersection of Data Engineering, MLOps, and AI Infrastructure
Deep knowledge of Spark internals, structured streaming, and performance tuning for large-scale data processing
Proven experience architecting end-to-end ML platforms for Traditional ML (Classic MLOps) while actively enabling the organization on Generative AI concepts
Strong background in building automated pipelines and ensuring system observability
Practical experience building infrastructure for Large Language Models, including managing the complexity of chaining models and tools
Solid experience serving models at low latency and high concurrency using containerized solutions
Ability to speak the language of AI/ML Engineers and effectively bridge the gap between experimental code and production systems
Expert level Python
Experience with PyTorch, Terraform, Terragrunt, Docker, Kubernetes, GitHub Actions, Datadog
Experience with Databricks AI Stack: MLflow, Mosaic AI, Unity Catalog, Feature Store, Databricks Model Serving, Vector Databases

Job Responsibility

Lead the evolution of our Machine Learning & AI Platform, designing the architecture for AI Agents and establishing patterns for Vector Databases
Act as a first mover: validate new Databricks features and integrate them into the platform
Write the guidelines for GenAI development, helping teams transition from notebook experiments to production-grade LLM applications
Design the Feature Store, manage the Model Registry, and set up the infrastructure for Vector Search and RAG (Retrieval Augmented Generation) workflows
Elevate the technical bar of the team, mentoring Staff and Senior engineers on design patterns, code quality, and architectural decisions
Translate complex requirements from ML Engineers and Data Scientists into robust engineering tickets and infrastructure roadmaps

What we offer

An attractive Base Salary
Participation in our Short Term Incentive plan (annual bonus)
Work From Anywhere: Enjoy up to 20 days a year of working from anywhere
A 24/7 Employee Assistance Program for you and your family

Fulltime

Senior Staff Data Engineer- ML & AI Platform

At Marktplaats, data is at the heart of everything we do, but Intelligence is wh...

Location

Netherlands , Amsterdam

Salary:

Not provided

Adevinta

Expiration Date

Until further notice

Requirements

10+ years of experience with a specific focus on the intersection of Data Engineering, MLOps, and AI Infrastructure
Deep knowledge of Spark internals, structured streaming, and performance tuning for large-scale data processing
Proven experience architecting end-to-end ML platforms for Traditional ML (Classic MLOps) while actively enabling the organization on Generative AI concepts
Strong background in building automated pipelines and ensuring system observability
Practical experience building infrastructure for Large Language Models, including managing the complexity of chaining models and tools
Solid experience serving models at low latency and high concurrency using containerized solutions
Ability to speak the language of AI/ML Engineers and effectively bridge the gap between experimental code and production systems

Job Responsibility

Lead the evolution of our Machine Learning & AI Platform, designing the architecture for AI Agents and establishing patterns for Vector Databases
Act as a first mover, validate new Databricks features and integrate them into the platform
Write the guidelines for GenAI development, helping teams transition from notebook experiments to production-grade LLM applications
Design the Feature Store, manage the Model Registry, and set up the infrastructure for Vector Search and RAG (Retrieval Augmented Generation) workflows
Elevate the technical bar of the team, mentoring Staff and Senior engineers on design patterns, code quality, and architectural decisions
Translate complex requirements from ML Engineers and Data Scientists into robust engineering tickets and infrastructure roadmaps

What we offer

An attractive Base Salary
Participation in our Short Term Incentive plan (annual bonus)
Work From Anywhere: Enjoy up to 20 days a year of working from anywhere
A 24/7 Employee Assistance Program for you and your family
A collaborative environment with an opportunity to explore your potential and grow

Fulltime

Senior Data Scientist - GenAI & ML

CRU Group is seeking a technically strong, hands-on Senior Data Scientist to joi...

Location

United Kingdom , London

Salary:

Not provided

CRU International

Expiration Date

Until further notice

Requirements

MSc or higher in a quantitative discipline such as econometrics, statistics, mathematics, physics, or similar
Expert-level Python skills and strong command of the core scientific stack, including Pandas, Scikit-learn, SciPy, and NumPy
3–5+ years of experience in data science, machine learning, econometrics, or a related technical field
Proven track record of independently delivering solutions, including model design, training, evaluation, deployment, and monitoring
Strong exposure to time-series forecasting or commodity data
Creative thinker with a robust approach to data and modelling
Hands-on experience working with machine learning and LLMs
Hands-on experience building AI applications beyond simple chatbot interfaces
Goal-oriented, with a high level of energy and enthusiasm
able to operate efficiently, effectively, and professionally in a fast-paced, dynamic, results-driven business environment

Job Responsibility

Build and deliver solutions across predictive analytics, machine learning, and LLM-based AI
Design, develop, and implement bespoke ML and AI agents and multi-step workflows using modern frameworks such as LangChain, LangGraph, or similar technologies
Develop robust, scalable, production-grade Python code
Partner with senior stakeholders to translate business needs into clear technical requirements and measurable outcomes
Own delivery end-to-end, including problem framing, data discovery, model development, evaluation, integration, deployment, monitoring, and iteration
Collaborate with global teams of analysts, product managers, product modellers, and engineers to deliver high-quality, reliable solutions
Mentor team members and contribute to raising standards for technical execution and delivery discipline
Stay current with developments in machine learning, statistical learning, generative AI, LLMs, and agentic workflows, and identify practical opportunities to apply these technologies within risk and trading services

What we offer

Competitive salary and flexible benefits package
Opportunities for professional growth and development as part of a global company
A collaborative and supportive work environment
The chance to work with industry-leading experts and over a diverse range of topics and projects

Fulltime

Senior Data Scientist – AI & ML | MLOps Enablement

The Developer Platform Organization’s mission is to accelerate the delivery of r...

Location

United States , Seattle

Salary:

166000.00 - 258000.00 USD / Year

Nordstrom

Expiration Date

Until further notice

Requirements

Bachelor’s, Master’s, or PhD in Statistics, Data Science, Computer Science, Engineering, or a related technical field required
10+ years of hands-on Data Science experience with production model delivery across multiple ML (classification, ranking, NLP, time-series, recommendation) and GenAI models
Deep expertise in model evaluation — defining metrics, thresholds, and evaluation pipelines for real-world production models
Experience with Feature Store design, feature engineering, and understanding of feature freshness, reuse, and drift across different model families
Proficiency in Python with experience writing clean, maintainable, production-quality ML code
Strong understanding of ML monitoring — data drift, prediction drift, and concept drift detection
Experience with experiment tracking and model lifecycle management
Ability to translate between DS practice and platform engineering — comfortable driving design decisions, authoring DS-native documentation, and engaging in technical design reviews
Self-directed
comfortable owning POC work end-to-end without a dedicated DS team structure

Job Responsibility

Run end-to-end POC validation for new platform capabilities — Feature Store, Endpoints, Model Evaluation, AutoML, BigQuery ML etc. — independently, before they reach DS teams at scale
Attend DS team planning and design sessions as an embedded practitioner
surface real workflow pain points and translate them into reusable MLOps platform requirements
Design and own the Model Evaluation Framework — defining metrics, thresholds, and evaluation pipelines for batch, online, and streaming use cases on Vertex AI
Build model-type-aware Feature Store schemas, endpoint configurations, and evaluation pipelines that accommodate the fundamentally different needs of different ML models
Lead benchmarking of Nordstrom’s platform against industry standards — SageMaker vs. Vertex AI — across feature parity, cost, and DS practitioner ergonomics
Author DS-native documentation, onboarding guides, and quickstart notebooks that lower the adoption barrier for new platform features
Contribute DS domain expertise to the emerging Vertex AI Agentic Platform — identifying DS workflow pain points as agent use cases and defining evaluation frameworks for agentic responses
Own model card standards — capturing what actually matters to a practitioner, not just governance checkboxes
Communicate complex trade-offs and platform decisions to technical and non-technical stakeholders across DS, engineering, and leadership

What we offer

Medical/Vision
Dental
Retirement
Paid Time Away
Life Insurance
Disability
Merchandise Discount
EAP Resources
401k
performance-based incentives/bonuses

Fulltime

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Senior Data Scientist / ML Engineer

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