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Machine Learning

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🔥 Senior Machine Learning Engineer

Posted about 1 hour ago

📍 Brazil, the U.S., and Canada

🧭 Full-Time

🔍 Payments

🔧 Requirements

Bachelor’s or Master’s degree in CS/Engineering/Data-Science or other technical disciplines.
Solid experience in DS/ML engineering.
Proficiency in programming languages such as Python, Scala, or Java.
Hands-on experience in implementing batch and real-time streaming pipelines, using SQL and NoSQL database solutions
Familiarity with monitoring tools for data pipelines, streaming systems, and model performance.
Experience in AWS cloud services (Sagemaker, EC2, EMR, ECS/EKS, RDS, etc.).
Experience with CI/CD pipelines, infrastructure-as-code tools (e.g., Terraform, CloudFormation), and MLOps platforms like MLflow.
Experience with Machine Learning modeling, notably tree-based and boosting models supervised learning for imbalanced target scenarios.
Experience with Online Inference, APIs, and services that respond under tight time constraints.
Proficiency in English.

💡 Responsibilities

Design the data-architecture flow for the efficient implementation of real-time model endpoints and/or batch solutions.
Engineer domain-specific features that can enhance model performance and robustness.
Build pipelines to deploy machine learning models in production with a focus on scalability and efficiency, and participate in and enforce the release management process for models and rules.
Implement systems to monitor model performance, endpoints/feature health, and other business metrics; Create model-retraining pipelines to boost performance, based on monitoring metrics; Model recalibration.
Design and implement scalable architectures to support real-time/batch solutions; Optimize algorithms and workflows for latency, throughput, and resource efficiency; Ensure systems adhere to company standards for reliability and security.
Conduct research and prototypes to explore novel approaches in ML engineering for addressing emerging risk/fraud patterns.
Partner with fraud analysts, risk managers, and product teams to translate business requirements into ML solutions.

AWS Backend Development Docker Python SQL Amazon RDS AWS EKS Frontend Development Java Kafka Kubernetes Machine Learning MLFlow Airflow Algorithms Data engineering Data science REST API Nosql Pandas Spark CI/CD Terraform Scala Data modeling English communication

Posted about 1 hour ago

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🔥 Principal Machine Learning Scientist (UK Remote)

Posted about 1 hour ago

📍 United Kingdom

🧭 Full-Time

🔍 Education

🔧 Requirements

Experience working with text data to build Deep Learning and ML models, both supervised and unsupervised. Experience with deep learning in other modalities such as vision and speech would be a strong bonus.
A strong understanding of the math and theory behind machine learning and deep learning.
Software engineering background with at least 3-5 years of experience (we use Python, SQL, Unix-based systems, git, and github for collaboration and review).
Machine / Deep Learning development skills, including experiment tracking (we use AWS SageMaker, Hugging Face, transformers, PyTorch, scikit-learn, Jupyter, Weights & Biases).
An understanding of Language Models, using and training / fine-tuning and a familiarity with industry-standard LM families.
Master's degree or PhD in Computer Science, Electrical Engineering, AI, Machine Learning, applied math or related field, with relevant industry experience, or outstanding previous achievements in this role. A Computer Science background is required as opposed to statistics or pure mathematics. We’re an applied science group leaning towards deep learning and therefore software development proficiency is a prerequisite.
Excellent communication and teamwork skills.
Fluent in written and spoken English.

💡 Responsibilities

Work with subject matter experts and product owners to determine what questions should be asked and what questions can be answered.
Work with subject matter experts to curate, generate, and annotate data, and create optimal datasets following responsible data collection and model maintenance practices.
Answer questions and make trainable datasets from raw data, using efficient SQL queries and scripting languages, visualizing when necessary.
Develop and tune Machine Learning models, following best practices to select datasets, architectures, and model parameters.
Utilize, adopt, and fine-tune Language Models, including third-party LLMs (through prompt engineering and orchestration) and locally hosted LMs.
Stay current in the field - read research papers, experiment with new architectures and LLMs, and share your findings.
Optimize models for scaled production usage.
Communicate insights, as well as the behavior and limitations of models, to peers, subject matter experts, and product owners.
Write clean, efficient, and modular code, with automated tests and appropriate documentation.
Stay up to date with technology, make good technological choices, and be able to explain them to the organization.

AWS Docker Python Software Development SQL Bash Data Analysis Frontend Development Git Machine Learning Numpy PyTorch Algorithms API testing Data science Data Structures REST API CI/CD RESTful APIs JSON Data visualization

Posted about 1 hour ago

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🔥 Director, Data Science (REMOTE: US)

Posted about 3 hours ago

📍 United States

💸 228100.0 - 325800.0 USD per year

🔍 Software Development

🏢 Company: Veeam Software👥 5001-10000💰 $2,000,000,000 Secondary Market 4 months ago🫂 Last layoff about 1 year agoVirtualization Data Management Data Center Enterprise Software Software Cloud Infrastructure

🔧 Requirements

Extensive experience in Data Analytics, Business Intelligence, and Reporting, with a strong focus on statistical methods
Advanced expertise in AI and Machine Learning, including model development, deployment, and designing AI-driven solutions for business processes
Proficient in technologies like Python, R, and TensorFlow, with formal training in Data Science and hands-on experience in machine learning libraries and data visualization techniques
Expertise in SQL queries, Excel, PowerPoint, and SaaS systems like Salesforce
Strong analytical skills and experience in AI-driven solutions
Experience with cloud computing platforms such as AWS, Azure, and Google Cloud
Proven ability to lead AI projects and implement innovative technologies that drive business value
Strong problem-solving skills and ability to handle complex datasets to extract actionable insights
Effective communication skills to articulate complex analytical concepts to technical and non-technical stakeholders

💡 Responsibilities

Lead and mentor a team of data scientists in developing advanced machine learning models, dashboards, and visualizations for predictive analytics and decision-making
Conduct and supervise statistical analyses and experiment-driven predictive modeling to extract actionable business insights, leveraging cutting-edge machine learning algorithms
Present analytical findings and recommendations to stakeholders and leadership, utilizing AI for enhanced data interpretation and driving strategic decisions
Identify and leverage data opportunities with cross-functional teams through AI-powered data mining techniques and unstructured problem-solving
Lead the deployment of secure, scalable data science solutions using Python, R, SQL, and AI frameworks to address complex business challenges
Implement and monitor automated anomaly detection systems using machine learning to swiftly identify and address issues
Design comprehensive experiments to validate models, ensuring robust and reliable outcomes
Drive innovation by continuously exploring and integrating new AI technologies and methodologies
Optimize operational workflows using AI and machine learning techniques, enhancing efficiency and productivity
Develop and refine complex algorithms to solve unstructured problems, applying deep learning and other advanced techniques
Ensure robust data quality and integrity with AI-driven cleaning and validation procedures
Communicate complex analytical concepts in a clear and concise manner to stakeholders, fostering understanding and collaboration across teams

AWS Python SQL Cloud Computing Data Analysis Data Mining Machine Learning Numpy Cross-functional Team Leadership Algorithms Data science Pandas Tensorflow Data visualization Data modeling Data analytics SaaS PowerPoint

Posted about 3 hours ago

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🔥 AI Engineer

Posted about 3 hours ago

📍 United States

💸 92300.0 - 169950.0 USD per year

🔍 Software Development

🔧 Requirements

Strong foundation in AI/ML concepts, such as model evaluation
Experience working with production AI/ML models
Experience creating LLM-powered services and features
Ability to write and maintain high quality code (Python) that is used by others
Ability and desire to learn and implement new techniques, topics, and technologies

💡 Responsibilities

Using the latest AI technologies to power specific features in our products
Evaluating, experimenting, and iterating on LLM prompts, agent workflows, and traditional ML models
Monitoring and maintaining production models
Working with Product and other Engineering teams to integrate our AI/ML features and services into our customer-facing products
Providing tactical and strategic input on technical matters related to production AI/ML
Learning new AI/ML techniques and best practices, and subject matter related to FinQuery's business
Working on a small, focused, awesome team to deliver outsized value to our customers using the latest AI/ML technologies

AWS Python Software Development Artificial Intelligence Data Analysis Machine Learning Algorithms CI/CD RESTful APIs

Posted about 3 hours ago

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🔥 AI Engineer

Posted about 3 hours ago

📍 Portugal

🔍 Software Engineering

🏢 Company: Broadvoice

🔧 Requirements

Master’s in Artificial Intelligence, Computer Science, Data Science, or a related field (or equivalent experience).
Proven experience working with LLMs, NLP and machine learning.
Strong experience with Node.js (JavaScript/TypeScript) and working with RESTful APIs and WebSockets.
Knowledge of vector databases (e.g., Pinecone, Weaviate, FAISS) and retrieval-augmented generation (RAG) methodologies.
Experience with fine-tuning and deploying models in cloud environments (AWS, Azure, or GCP) is a plus.
Passion for exploring and implementing the latest advancements in AI and LLMs.
Critical thinking and problem-solving mindset.
Strong communication skills.

💡 Responsibilities

Research and experiment with LLMs (e.g., OpenAI, Anthropic, Mistral, Llama) to identify potential applications in automation, customer interactions, and internal processes.
Develop and fine-tune LLM-powered solutions, focusing on areas such as chatbots, intelligent assistants, and knowledge retrieval.
Apply prompt engineering techniques to improve model performance for Broadvoice’s use cases.
Explore and implement retrieval-augmented generation (RAG) approaches, integrating LLMs with structured company knowledge bases.
Collaborate with engineering and product teams to integrate AI-powered features into Broadvoice’s products and services.
Stay updated on emerging AI trends and assess third-party AI tools that could accelerate development.

AWS Node.js Artificial Intelligence Cloud Computing GCP Machine Learning Azure RESTful APIs

Posted about 3 hours ago

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🔥 Principal, Product Manager - Canada

Posted about 3 hours ago

📍 Canada

🧭 Full-Time

🔍 Accounting

🔧 Requirements

Bachelor’s degree in Information Technology, or equivalent work experience and education; Master’s degree is a plus.
Experience in ML/AI, development or technical roles, or experience in Taxation and Accounting technology

💡 Responsibilities

Being a strong influencer of Ascend’s AI strategy, in partnership with the rest of the AI Team.
Working backward from customer needs, develop and communicate your product vision to Ascend leadership and the AI team
Develop a 12-month prioritized roadmap in collaboration with Engineering.
Own the product lifecycle for your product area, from ideation to launch, ensuring continuous iteration and improvement.
Identify and drive large-scale transformation opportunities within your product area.
Develop and execute product strategies that enhance Ascend’s operating margins.
Align and manage dependencies between product areas to ensure a cohesive roadmap.
Provide clear, structured input to Engineering to ensure smooth product development.
Ensure Engineering priorities align with business objectives.
Develop strong ML/LLM hypotheses based on customer research and deep industry understanding.
Partner with AI Engineering to define and prioritize ML/LLM experiments.
Improve and iterate on product launch mechanisms while defining and tracking key metrics post-launch to drive continuous improvement.
Communicate outcomes clearly, adjust priorities based on results, escalate and recommend pivots when needed.

AWS Data Analysis Machine Learning Product Management Cross-functional Team Leadership Product Development Communication Skills Agile methodologies RESTful APIs Data visualization Customer Success

Posted about 3 hours ago

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🔥 Senior Product Manager, AI Figure Generation

Posted about 4 hours ago

📍 US; CA

🧭 Full-Time

🔍 SaaS

🏢 Company: BioRender👥 101-250💰 $15,319,133 Series A almost 2 years agoLife Science Graphic Design Software

🔧 Requirements

5+ years of direct ML and/or AI product management experience, ideally in a fast growing SaaS startup environment.
You’ve built an AI product and know how to apply AI/ML technology to deliver real user value.
You have a demonstrated ability to make your vision a reality.
You are an expert at bringing together qualitative user insights and quantitative data to make the most effective product decisions.

💡 Responsibilities

Drive development, communication, and execution of the vision for our AI-backed figure generation and illustration capabilities.
Own and be accountable for the product roadmap, measurement of success, and operations for our AI figure generation features.
Identify opportunities for other product teams at BioRender to take advantage of the work of your team and influence them to do that.

Artificial Intelligence Data Analysis Machine Learning Product Management Cross-functional Team Leadership Product Development Product Analytics Communication Skills SaaS

Posted about 4 hours ago

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🔥 Healthcare Data Analytics Manager (Mexico - Remote)

Posted about 5 hours ago

📍 Mexico

🔍 Healthcare

🏢 Company: FlexTal Staffing LLC

🔧 Requirements

Minimum of 5-8 years direct experience with 3+ years of management experience.
Working knowledge of Microsoft SQL
ETL development and management
Strong statistical knowledge for interpreting clinical and operational data
Strong knowledge of Microsoft Outlook and other Office applications, especially Excel and PowerPoint
Point Click Care, Python/R & PowerBI experience
Experience in healthcare, insurance, or senior living industries

💡 Responsibilities

Oversee the collection, cleaning, and storage of healthcare data from various sources (electronic health records, billing systems, patient surveys, etc.).
Ensure compliance with regulations such as HIPAA (Health Insurance Portability and Accountability Act) to maintain patient privacy.
Integrate data from disparate sources (clinical, financial, and operational) to create comprehensive datasets that can inform decision-making.
Work on transforming raw data into a structured format that can be analyzed (using tools like SQL, Python, or ETL processes).
Use statistical methods and data analytics tools (like Python, R, Excel, or Power BI) to analyze data and extract meaningful insights.
Develop and automate dashboards and reports to monitor key performance indicators (KPIs) related to patient care, hospital performance, and operational efficiency.
Leverage machine learning and predictive models to forecast patient outcomes, readmission rates, or operational bottlenecks.
Use historical data to identify trends and patterns that can help improve clinical and administrative decision-making.

Python SQL Data Analysis ETL Machine Learning Microsoft Power BI Microsoft SQL Server Data engineering Microsoft Excel Agile methodologies Data visualization Data modeling Data analytics Data management

Posted about 5 hours ago

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🔥 Data Scientist

Posted about 5 hours ago

📍 South Africa

🔍 Finance & Technology

🏢 Company: JUMO👥 251-500💰 $120,000,000 over 3 years agoMobile Payments Big Data Financial Services Banking InsurTech FinTech

🔧 Requirements

A bachelor's degree with a strong quantitative component (e.g. Economics, Physics, Engineering, Software engineering, etc.).
Minimum 3-5 years of experience filling a similar role in Finance & Technology.
Strong data wrangling skills using SQL and coding in python.
Strong interest in software development.
An ability to interpret problems, and simplify them to their essentials.
The desire to innovate, be creative and work on challenging problems.
Experience using software development practices like git, CI/CD, etc.

💡 Responsibilities

Analyse, transform, augment and build datasets to convert financial and behavioural data into features and dimensions that allow us to more easily and accurately extract insights.
Use your coding skills to contribute to our team tooling and automate processes as much as possible.
Design and develop models of our real world systems and client behaviours to help inform our decision making. This includes, but is not limited to, forecasting, simulating products or systems, testing decline strategies, and optimising client experience.
Analyse end user requirements to understand and communicate what our stakeholders (for example, fellow analysts, portfolio managers, or partners) need, and what we can deliver to match those expectations.
Derive and communicate insights to our stakeholders.

AWS Python SQL Cloud Computing Data Analysis Git Machine Learning Algorithms Data science Analytical Skills CI/CD Problem Solving RESTful APIs Data visualization Financial analysis Data modeling Finance

Posted about 5 hours ago

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🔥 Machine Learning Developer / Engineer (EST Hours) - Remote

Posted about 7 hours ago

📍 South Africa

🔍 Healthcare

🏢 Company: ISTA Personnel Solutions

🔧 Requirements

Strong problem-solving and coding skills.
Experience building machine learning models.
Python skills for data analysis and building dashboards with libraries like Dash, Streamlit, Panel, Bokeh.

💡 Responsibilities

Develop and implement machine learning models to solve complex business problems from the ground up.
Use algorithms such as Random Forest, Gradient Boosting, and AutoML to enhance model performance.
Ensure models are scalable and maintainable.
Perform detailed data analysis to extract meaningful insights.
Conduct feature engineering to improve model accuracy.
Validate and clean data to ensure high-quality datasets for model training.
Communicate findings and recommendations to stakeholders in a clear and concise manner.
Collaborate with team members to integrate models into existing systems and workflows.
Create dashboards and visualizations using Python libraries such as Dash, Streamlit, Panel, and Bokeh.
Present data-driven insights through interactive and user-friendly dashboards.
Provide regular reports on model performance and business impact.
Apply machine learning techniques to healthcare-specific problems.

Python Data Analysis Machine Learning Data visualization Data modeling

Posted about 7 hours ago

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