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Machine Learning

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1,780 jobs found.

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🔥 Data Scientist (Applied Machine Learning)

Posted about 1 hour ago

📍 Europe

🧭 Full-Time

🔍 Hospitality

🏢 Company: Nory

🔧 Requirements

A scientific approach to problem solving based on crafting and testing hypotheses
The ability to write clean and maintainable python code
Real world experience deploying algorithms into production
Strong fundamentals in ML theory
Familiarity with cloud infrastructure

💡 Responsibilities

Design, build and deploy production new machine learning algorithms
Monitor, maintain and iterate on existing algorithms
Work closely with product and engineering on collaborative feature releases
Contribute to the wider data and tech community at Nory

Python Cloud Computing Machine Learning MLFlow Numpy Algorithms Data science Data Structures Pandas RESTful APIs

Posted about 1 hour ago

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🔥 Product Data Scientist

Posted about 2 hours ago

📍 United States, Canada

🧭 Full-Time

💸 140000.0 - 180000.0 USD per year

🔍 Video Gaming

🏢 Company: thatgamecompany👥 101-250💰 about 3 years agoDeveloper Tools Video Games Console Games Family MMO Games Social Network Mobile Online Games

🔧 Requirements

3+ Years of Experience applying Data Science methodologies to product development
Strong understanding of machine learning and statistical methods, including classical ML, deep learning, NLP, and anomaly detection.
Expertise in statistical concepts such as experimental design, hypothesis testing, regression, classification, and clustering
Proficiency in writing clean, efficient code in Python, Java, or Typescript
Experience writing optimized SQL Queries to build and analyze datasets
Familiarity with modern Cloud Platforms (preferably GCP)
Exposure to big data processing tools like BigQuery, Redshift, Snowflake, Spark, and Beam
Strong communication skills, desire to understand the data you’re using, and the ability to explain what you built and why you built it
Willingness to continuously learn, adapt, and step outside of your comfort zone.

💡 Responsibilities

Comb through large sets of game telemetry data to uncover player relationships, feature usage trends, security threats, inefficiencies, and opportunities to improve the player or developer experience.
Design and test innovative solutions to improve new player retention through data-driven insights and automation
Develop novel solutions to identify, surface, and mitigate non-human bot activity
Translate data-driven solutions into product features to automate and share our innovations
Give a presentation to help talk through some unintuitive discoveries from one of your data models

Python SQL Cloud Computing Data Analysis Data Mining GCP Kubernetes Machine Learning Data science Spark Data visualization Data modeling

Posted about 2 hours ago

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🔥 Machine Learning Ops Engineer

Posted about 2 hours ago

📍 US

🧭 Full-Time

🔍 Software Development

🏢 Company: Weave👥 501-1000💰 $70,000,000 Series D over 5 years agoMedical SaaS VoIP Unified Communications Small and Medium Businesses Software

🔧 Requirements

5+ years of experience in any structured back-end language, i.e. Go, Java or Python (Go and Python experience is a plus).
Experience moving and storing TBs of data or 100M’s to 10B’s of records.
Demonstrated experience with common MLOps technologies such as Python, Jupyter, Workflow Engines (Dagster, MLFlow, KubeFlow, etc), DVC, Triton Server, LLMs, Postgres, and others.
Experience with data labelling or annotation for audio or NLP use cases.
Understanding of distributed systems and building scalable, redundant, and observable services.
Expertise in designing and architecting systems for distributed data sets and services
Experience building solutions to run on one or more of the public clouds (e.g., AWS, GCP, etc.).
Experience providing stable well designed libraries and SDKs for internal use.
Demonstrated track record of delivering complex projects on time and have experience working in enterprise-grade production environments.

💡 Responsibilities

Design and Develop machine learning infrastructure, tooling, and models to help teams deliver world class experiences.
Help product and development teams understand the data lifecycle and the inherent experimental nature of machine learning.
Build internal products and platforms to enable teams to incorporate AI into their features and customer facing products.
Consult with teams to help them understand common patterns, anti-patterns, and tradeoffs of machine learning. Guide them through creating excellent customer experiences end to end.
Build scalable, resilient services to support data integration, event processing, and platform extensions.
Contribute to the continued evolution of product functionality that services large amounts of data and traffic.
Write code that is high-quality, performant, sustainable, and testable while holding yourself accountable for the quality of the code you produce.
Coach and collaborate inside and outside the team. You enjoy working closely with others - helping them grow by sharing expertise and encouraging best practices.
Work in a cloud environment, considering the implementation of functionality through several distributed components and services.
Work with our stakeholders to translate product goals into actionable engineering plans.

AWS Backend Development Docker PostgreSQL Python SQL Cloud Computing Data Analysis GCP Git Kubernetes Machine Learning MLFlow API testing Data engineering Data science Go REST API CI/CD DevOps Microservices Data visualization Data modeling

Posted about 2 hours ago

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🔥 Senior Data Scientist | CARE

Posted about 3 hours ago

📍 Brazil, Portugal

🔍 Wellness

🏢 Company: Wellhub

🔧 Requirements

Master’s degree or PhD in Computer Science, Data Science, Machine Learning, Statistics, or a related field.
Proficiency in Python and experience with machine learning frameworks such as PyTorch, TensorFlow, or similar.
Strong understanding of generative AI architectures, including transformers and attention mechanisms.
Experience in multi-agent systems and LLMs.
Strong problem-solving abilities, with a focus on experimental design and data analysis.
Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
Have clear scientific thinking and a passion for integration R&D and cutting-edge technology into a product
Prior experience in Python and SQL

💡 Responsibilities

Model Development & Fine tuning: Understanding of state-of-the-art deep learning techniques, such as Transformers architectures and attention mechanisms, and knowledge of fine-tuning LLMs for enhanced model performance, using techniques such as LoRA, QLoRA, among others.
Function Calling & Tool Use: Design and implement structured function calling mechanisms within LLMs to enable dynamic interactions with APIs, databases, and retrieval-augmented generation (RAG) pipelines.
Prompt Engineering: Craft clear instructions that help our models understand exactly what we need, creating reusable templates and testing against edge cases.
Data Preparation: Preprocess, analyse, and curate high-quality datasets to train and fine-tune both embedding and generative models.
Evaluation and Testing: Develop robust evaluation frameworks to assess agentic AI performance, combining automated evaluation (LLM-as-judge), adversarial testing, human-in-the-loop evaluations, and custom behavioral metrics.
LLM Observability: Establish monitoring systems that track LLM behavior in production, capturing key metrics around information retrieval, hallucinations, and latency.
Research and Innovation: Stay current with the latest research in generative AI,, share insights with the team, test promising approaches, and help make us better.
Deployment: Collaborate with engineering teams to deploy models in scalable and efficient production environments.

AWS Python SQL Data Analysis Machine Learning PyTorch Algorithms Amazon Web Services Data science Tensorflow CI/CD RESTful APIs Data visualization Data modeling

Posted about 3 hours ago

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🔥 Software Engineer (Backend/Data)

Posted about 3 hours ago

📍 USA

🧭 Full-Time

💸 100000.0 - 175000.0 USD per year

🔍 Healthcare

🏢 Company: Fathom👥 51-100 Accounting Business Intelligence Finance Analytics Software

🔧 Requirements

2+ years of software engineering experience in a company/production setting
Relevant experience developing backend, integrations, data pipelining, infrastructure, etc. projects in a production setting
Problem solving skills and first principles thinking
Strong computer science principles including: algorithms, databases (SQL and NoSQL), logic, etc.
Hands-on backend coding and systems design using best practices in a company setting
Effective communication and exceptional collaboration skills

💡 Responsibilities

Developing data infrastructure to ingest, sanitize and normalize a broad range of medical data, such as electronics health records, journals, established medical ontologies, crowd-sourced labelling and other human inputs
Building performant and expressive interfaces to the data
Creating infrastructure to help us not only scale up data ingest, but large-scale cloud-based machine learning

AWS Backend Development Python SQL Cloud Computing Machine Learning Algorithms Data engineering Data Structures Postgres Nosql CI/CD RESTful APIs Data modeling Software Engineering Data management

Posted about 3 hours ago

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🔥 Senior AI Engineer

Posted about 4 hours ago

📍 Canada

🧭 Full-Time

🔍 Software Development

🏢 Company: Procurify👥 101-250💰 $20,000,000 5 months agoCloud Computing SaaS Supply Chain Management Enterprise Software FinTech Software Procurement

🔧 Requirements

4-6+ years in a similar Machine Learning or Data Scientist role, including 2+ years experience in LLMs.
Proven experience as the first ML engineer or a similar role, demonstrating a strong ability to build ML and AI systems from the ground up.
Demonstrated experience building AI apps in production.
Proficiency in machine learning frameworks and libraries (e.g. Tensorflow, PyTorch, scikit-learn, Pandas)
Experience in building with LLMs such as GPT, Claude, Llama etc and strong understanding of LLM architectures and tools (Llamaindex, vector databases, Transformers, Langchain etc)
Experience with ETL/ELT tools, Data Lakehouse tech (Databricks, Python, Apache Spark, Hive, Parquet) and advanced SQL knowledge.
Strong programming skills in Python and familiarity with additional languages and tools commonly used in ML engineering.
Comfortable leading by example and using influence to drive collaboration, documentation, and knowledge sharing across teams and with a broad range of stakeholders.
Able to demonstrate initiative, work independently, and thrive with autonomy while collaborating across teams in a culture of priority setting and moving forward with urgency in alignment with our organizational strategy
Adept at focusing on multiple competing priorities, solving unique and complex technical problems, and persistently resolving blockers to progress
Familiar with DevOps and MLOps principles such as design for manageability and root cause analysis
Familiar working within leading software development best practices such as scrum/kanban, CI/CD, and test automation
A strong driver to stay ahead of the curve with GenAI research and apply those insights to build real-world applications.

💡 Responsibilities

Develop and refine autonomous agents leveraging generative AI to automate and streamline user workflows, enhancing operational efficiency and user experience.
Design, create, evolve, and maintain scalable and efficient machine learning systems including, data pipelines, model training, deployment, and monitoring frameworks.
Integrate and leverage Large Language Models (LLMs) to develop advanced NLP features, including but not limited to chatbots, workflow automation agents and data analysis tools using state-of-the-art models (e.g. OpenAI, Anthropic, open source models).
Develop and enhance systems to deliver personalized experiences to our users, utilizing advanced machine learning and AI technologies to derive engagement and satisfaction.
Partner across Product and Engineering teams on requirements to create product capabilities that fundamentally rely on AI and Machine Learning.
Drive conversations within Engineering to improve and optimize the source data models, integration of the ML capabilities including those in our product platform.
Identify, design, and implement internal process improvements, including automation for data quality control and data validation, improved data delivery, and scalability.
Mentor other engineers, imparting best practices and institutionalizing efficient processes to foster growth and innovation within the team.

Python SQL ETL Machine Learning Numpy PyTorch Data engineering Data science Pandas Spark Tensorflow CI/CD RESTful APIs DevOps

Posted about 4 hours ago

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🔥 Senior Backend Software Engineer - GenAI, Conversational Experience (open to remote across ANZ)

Posted about 4 hours ago

📍 Australia, New Zealand

🧭 Full-Time

🔍 Software Development

🔧 Requirements

5+ years of backend engineering experience, ideally working with large-scale distributed systems.
Strong proficiency in Java or Kotlin and experience with microservices architecture.
Experienced with cloud platforms (AWS, GCP, or Azure) and infrastructure-as-code tools like Terraform.
Hands-on experience with real-time data processing and event-driven architectures (Kafka, Pub/Sub, etc.).
Knowledge of integrating machine learning models into production environments.
Passionate about AI-powered experiences and conversational interfaces.
Strong problem-solving skills and the ability to work in fast-paced, iterative development cycles.

💡 Responsibilities

Designing, developing, and optimizing high-performance backend services that power Canva’s Conversational AI experiences.
Working closely with AI researchers and ML engineers to integrate cutting-edge machine learning models into production systems.
Architecting scalable APIs and infrastructure to handle millions of AI-driven interactions.
Implementing and maintaining real-time data pipelines that enhance AI-driven user experiences.
Ensuring high availability and reliability of AI-powered services through best practices in observability, monitoring, and incident response.
Staying at the forefront of AI and backend development trends, bringing new ideas and innovations to the team.

AWS Backend Development Docker Cloud Computing GCP Java Kafka Kotlin Machine Learning API testing Azure Terraform Microservices

Posted about 4 hours ago

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🔥 Senior Systems Engineer

Posted about 4 hours ago

📍 US

🧭 Full-Time

💸 80001.0 - 120000.0 USD per year

🔧 Requirements

Five (5) or more years of professional experience in AI is preferred, but may accept experience in related fields (data science, machine learning) with a focus on federal contracting or government environments.
Demonstrated success in developing and delivering RFI/RFP responses and other technical documentation for enterprise-scale solutions.
Hands-on experience with frameworks and methodologies for responsible AI, data, and related governance, risk, and compliance topics.
Strong understanding of AI, ML, and data best practices, capabilities, and market trends.
Familiarity with federal acquisition processes and compliance requirements.
Outstanding written and verbal communication skills, with an ability to translate complex technical concepts into clear, compelling narratives.
Exceptional organizational skills and attention to detail, particularly in the context of large-scale documentation efforts.
Strong interpersonal skills to build and maintain relationships with diverse stakeholders.
Proven ability to work cross-functionally, managing competing priorities in a dynamic environment.

💡 Responsibilities

Develop and execute strategies to support the AI & Data Portfolio and enterprise-wide objectives with effective RFI and RFP responses.
Build and communicate a roadmap of planned deliverables for the upcoming fiscal year.
Create comprehensive methodologies for responsible AI practices, data governance, AI capabilities, and ML implementation.
Support the creation of high-quality documentation, including white papers, frameworks, and briefs that capture the portfolio’s capabilities and align with portfolio and enterprise strategic priorities.
Develop reusable templates and content to streamline writing development.
Collaborate within the portfolio and across other teams and portfolio areas to ensure cohesion across Digital Innovation Factory Solutions Engineering efforts.

Project Management Agile Artificial Intelligence Data Analysis Machine Learning Data science Communication Skills RESTful APIs Strategic thinking Data modeling

Posted about 4 hours ago

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🔥 Senior Product Manager – Semantic Analytics

Posted about 4 hours ago

📍 Germany

🔍 Enterprise conversations

🏢 Company: LivePerson👥 501-1000💰 $100,000,000 Post-IPO Debt 11 months ago🫂 Last layoff over 4 years agoInternet Customer Service Artificial Intelligence (AI)Business Intelligence Software

🔧 Requirements

7+ years of product management experience, preferably in enterprise analytics, AI, or SaaS environments.
Deep understanding of NLP/NLU, categorization frameworks, and semantic analytics methodologies.
Proven track record in launching data-rich, customer-facing products with measurable impact.
Strong analytical thinking — adept at defining success metrics, testing hypotheses, and partnering with technical teams.

💡 Responsibilities

Own the vision, strategy, and roadmap for Semantic Analytics across our data platform.
Define product KPIs, success metrics, and GTM strategies for Intent Analyzer and Analytics Studio.
Collaborate closely with Engineering, Data Science, Design, and GTM teams to deliver scalable, high-value solutions.
Translate customer insights into actionable features and drive adoption through strong enablement.
Identify opportunities to integrate Generative AI into analytics workflows and conversational intelligence products.

SQL Data Analysis Machine Learning Product Management Data science RESTful APIs

Posted about 4 hours ago

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🔥 Data Scientist

Posted about 4 hours ago

📍 United States

🔍 Financial Information

🏢 Company: SmartAsset👥 251-500💰 Secondary Market over 3 years agoMarketplace Financial Services Personal Finance Wealth Management Finance FinTech

🔧 Requirements

Proficient in Python and SQL
Strong data visualization and analysis skills (pandas, numpy, matplotlib, scikit learn, tensorflow, etc)
Working experience with the development and deployment of predictive models, with an emphasis on time series and categorization models
Strong statistical foundation

💡 Responsibilities

Develop and deploy machine learning models that will drive business decisions and improve user experience
Utilize your strong problem-solving skills, programming know-how, and business analytics to solve real-world problems at scale
Access and analyze a variety of data to perform descriptive, predictive and prescriptive analytics, working closely with stakeholders from different teams (Sales, Marketing, Product, and Technology)
Be responsible for creating stable models that will run in a production environment

Python SQL Git Machine Learning Numpy Data science Pandas Tensorflow Data visualization

Posted about 4 hours ago

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