Junior Data Scientist / Machine Learning Engineer Job at Red Hibbert Group

Principal Machine Learning System Engineer

As a Principal Machine Learning Systems Engineer, you will lead the design, deve...

Location

United States , Seattle; San Francisco

Salary:

190300.00 - 305600.00 USD / Year

Atlassian

Expiration Date

Until further notice

Requirements

Lead the design, development, and deployment of scalable machine learning (ML) systems and infrastructure
Collaborate closely with data scientists, software engineers, and product teams
Optimize model performance
Ensure system reliability
Implement efficient data pipelines
Drive architectural decisions for high-performance computing and cloud-based ML platforms
Mentor junior engineers
Promote best practices in ML operations (MLOps)
Stay updated on emerging technologies

Job Responsibility

Translate complex ML models into production-ready solutions
Ensure scalability and security
Deliver robust, scalable, and efficient machine learning solutions that support business growth and innovation

What we offer

Health coverage
Paid volunteer days
Wellness resources

Fulltime

Senior Machine Learning Engineer

As a Senior Machine Learning Engineer in the Central AI team, you will build and...

Location

Australia , Sydney

Salary:

Not provided

Atlassian

Expiration Date

Until further notice

Requirements

Master or PhD in a quantitative subject (Statistics, Mathematics, Computer Science, Operations Research, or relevant work experience)
3+ years of related industry experience in the data science domain
Expertise in Python or Java with and the ability to write performant production-quality code, familiarity with SQL, knowledge of Spark and cloud data environments (e.g. AWS, Databricks)
Experience building and scaling machine learning models in business applications using large amounts of data
Ability to communicate and explain data science concepts to diverse audiences, craft a compelling story
Focus on business practicality and the 80/20 rule
very high bar for output quality, but recognize the business benefit of "having something now" vs "perfection sometime in the future"
Agile development mindset, appreciating the benefit of constant iteration and improvement

Job Responsibility

Build and maintain the core infrastructure to allow machine learning engineers and data scientists to develop, train, evaluate, deploy, and operate Machine Learning models and pipelines
Use software development expertise to solve difficult problems, tackling complex infrastructure and architecture challenges
Design system and model architectures, conducting rigorous experimentation and model evaluations, and providing guidance to junior ML engineers
Lead other engineers to drive involved projects from technical design to launch
Collaborate with other teams and internal customers to set expectations, gather input and communicate results

What we offer

Health and wellbeing resources
Paid volunteer days

Fulltime

Junior Data Scientist - AI

Hewlett Packard Enterprise (HPE) is seeking a Junior Data Scientist - AI to desi...

Location

United States , San Juan

Salary:

Not provided

Hewlett Packard Enterprise

Expiration Date

Until further notice

Requirements

Bachelor's degree in computer science, engineering, information systems, or closely related quantitative discipline
typically, 2-4 years’ experience
strong background in statistical and machine learning techniques such as anomaly detection, clustering and ranking of events, time series analysis, event stream mining, hypothesis testing, causal inference, deep learning
great at communicating concepts and results
strong data visualization skills
expert Python coder (PySpark, Scikit-learn)
experience with software engineering best practice
relevant industry experience in data science, machine learning
experience with online learning algorithms, reinforcement learning, semi-supervised learning, or mixed time-series/event streams
experience with Agentic AI

Job Responsibility

Works with domain experts to identify and formalize machine learning problems for wireless and wired network diagnostics, root causing, problem remediation, and optimization
discover new problem signatures in customer networks
design, implement, and validate machine learning algorithms on big data
guide and oversee deployment of implemented machine learning solutions and monitor their operation
use Agentic AI to solve networking problems
analyses the feature specifications and determines the required coding, testing, and integration activities
designs and develops moderate to complex cloud application modules per feature specifications adhering to security policies
identifies debugs and creates solutions for issues with code and integration into application architecture
develops and executes comprehensive test plans for features adhering to performance, scale, usability, and security requirements
deploy cloud-based systems and applications code using continuous integration/deployment (CI/CD) pipelines to automate cloud applications' management, scaling, and deployment

What we offer

comprehensive suite of benefits supporting physical, financial and emotional wellbeing
specific programs catered to helping reach career goals
unconditional inclusion.

Fulltime

AI and Machine Learning Engineer

AI and Machine Learning Engineer role at Hewlett Packard Enterprise focusing on ...

Location

India , Bangalore

Salary:

Not provided

Hewlett Packard Enterprise

Expiration Date

Until further notice

Requirements

Bachelor's degree in computer science, engineering, data science, machine learning, artificial intelligence, or closely related quantitative discipline
Master's degree is desirable
Typically 5-7 years' experience
Deep understanding of machine learning algorithms such as linear regression, decision trees, support vector machines, random forests, deep learning models, and reinforcement learning
Strong foundation in mathematics and statistics including linear algebra, calculus, probability theory, and statistical concepts
Proficiency in programming languages such as Python, R, or Java
Experience with software engineering best practices, version control systems, and software development methodologies
Knowledge of libraries and frameworks like TensorFlow, PyTorch, sci-kit, and Keras
Proficiency in using agentic frameworks like langGraph or similar frameworks
Knowledge in lineage tracking of agentic architectures

Job Responsibility

Conduct advanced research in AI and machine learning
Stay up to date with latest advancements in the field
Explore emerging technologies and identify opportunities to apply cutting-edge techniques
Evaluate traditional AI/ML and Gen-AI based applications during development phase and in production
Design solutions considering scalability, performance, and maintainability
Provide technical guidance and mentorship to junior team members
Collaborate with cross-functional teams including product managers, data scientists, and business analysts
Drive continuous improvement and innovation in AI and machine learning practices
Evaluate and integrate third-party tools or services
Facilitate design review sessions

What we offer

Health & Wellbeing benefits
Personal & Professional Development programs
Unconditional Inclusion environment
Comprehensive suite of benefits supporting physical, financial and emotional wellbeing

Fulltime

Senior Machine Learning Engineer, Personalization and Recommendations

As a Senior Machine Learning Engineer on the Personalization & Recommendations t...

Location

United States , San Francisco

Salary:

183360.00 - 248000.00 USD / Year

EdTech Jobs

Expiration Date

Until further notice

Requirements

5+ years of experience in applied machine learning or ML-heavy software engineering, with a strong focus on personalization, ranking, or recommendation systems
Demonstrated impact improving key metrics such as CTR, retention, or engagement through recommender or search systems in production
Strong hands-on skills in Python and PyTorch, with expertise in data and feature engineering, distributed training and inference on GPUs, and familiarity with modern MLOps practices — including model registries, feature stores, monitoring, and drift detection
Deep understanding of retrieval and ranking architectures, such as Two-Tower models, deep cross networks, Transformers, or MMoE, and the ability to apply them to real-world problems
Experience with large-scale embedding models and vector search, including FAISS, ScaNN, or similar systems
Proficiency in experiment design and evaluation, connecting offline metrics (AUC, NDCG, calibration) with online A/B test outcomes to drive product decisions
Clear, effective communication, collaborating well with product managers, data scientists, engineers, and cross-functional partners
A growth and mentorship mindset, helping elevate team quality in modeling, experimentation, and reliability
Commitment to responsible and inclusive personalization, ensuring our systems respect learner privacy, fairness, and diverse goals

Job Responsibility

Design and implement personalization models across candidate retrieval, ranking, and post-ranking layers, leveraging user embeddings, contextual signals and content features
Develop scalable retrieval and serving systems using architectures such as Two-Tower models, deep ranking networks, and ANN-based vector search for real-time personalization
Build and maintain model training, evaluation, and deployment pipelines, ensuring reliability, training–serving consistency, observability, and robust monitoring
Partner with Product and Data Science to translate learner objectives (engagement, retention, mastery) into measurable modeling goals and experiment designs
Advance evaluation methodologies, contributing to offline metric design (e.g., NDCG, CTR, calibration) and supporting rigorous A/B testing to measure learner and business impact
Collaborate with platform and infrastructure teams to optimize distributed training, inference latency, and serving cost in production environments
Stay informed on industry and research trends, evaluating opportunities to meaningfully apply them within Quizlet’s ecosystem
Mentor junior and mid-level engineers, supporting technical growth, experimentation rigor, and responsible ML practices
Champion collaboration, inclusion, curiosity, and data-driven problem solving, contributing to a healthy and productive team culture

What we offer

20 vacation days
Competitive health, dental, and vision insurance (100% employee and 75% dependent PPO, Dental, VSP Choice)
Employer-sponsored 401k plan with company match
Access to LinkedIn Learning and other resources to support professional growth
Paid Family Leave, FSA, HSA, Commuter benefits, and Wellness benefits
40 hours of annual paid time off to participate in volunteer programs of choice

Fulltime

Machine Learning Research Engineer

You will be part of Kiddom’s Data Science team, building the foundation of our s...

Location

United States , San Francisco; New York

Salary:

175000.00 - 250000.00 USD / Year

Kiddom

Expiration Date

Until further notice

Requirements

Have 5+ years of industry experience applying machine learning to solve real-world problems with large, complex datasets, with 1–2 years in a technical leadership role
Proven track record designing, evaluating, and deploying ML/AI systems in production environments that drive measurable business impact, ideally in recommendation, personalization, search, or workflow optimization
Strong programming skills in Python and fluency in data manipulation (SQL, Pandas) and common ML toolkits (scikit-learn, XGBoost, TensorFlow/PyTorch)
Strong analytical skills and ability to break down complex problems into measurable hypotheses and experiments
Excellent communication skills with a history of cross-functional collaboration with product, design, and engineering stakeholders

Job Responsibility

Architect and scale machine learning systems for search, personalization, and recommendations that power Kiddom’s teacher helper and insight engine
Develop evaluation-first development workflows to measure how models improve teaching efficiency, lesson planning, and student learning outcomes
Fine-tune machine learning models with feedback signals from teachers and students to align outputs with instructional goals and classroom needs
Design intelligent discovery pipelines that combine semantic retrieval, curriculum alignment, and real-time personalization
Build agentic assistants that help teachers plan lessons, adapt instruction, and reduce repetitive tasks
Collaborate closely with product managers, designers, and curriculum experts to translate high-level educational goals into scalable ML-powered systems
Coach and mentor junior ML engineers and data scientists, fostering technical and professional growth

What we offer

Competitive salary
Meaningful equity
Health insurance benefits: medical (various PPO/HMO/HSA plans), dental, vision, disability and life insurance
One Medical membership (in participating locations)
Flexible vacation time policy (subject to internal approval). Average use 4 weeks off per year
10 paid sick days per year (pro rated depending on start date)
Paid holidays
Paid bereavement leave
Paid family leave after birth/adoption. Minimum of 16 paid weeks for birthing parents, 10 weeks for caretaker parents. Meant to supplement benefits offered by State
Commuter and FSA plans

Fulltime