Data Engineer / Data Scientist – MLOps & Machine Learning Job at Beacon Hill (Charlotte)

Data Engineer-Data Scientist – MLOps & Machine Learning

Seeking a highly analytical and hands-on Data Engineer / Data Scientist with str...

Location

United States , Suffolk

Salary:

70.00 USD / Hour

Beacon Hill

Expiration Date

Until further notice

Requirements

5+ years of hands-on experience as a Data Engineer or Data Scientist in large-scale, cloud-based data environments
Strong experience building or supporting MLOps workflows in Databricks
Hands-on experience with MLflow, including experiment tracking, model registry, and deployment workflows
Strong understanding of machine learning fundamentals and model lifecycle management
Solid data science foundation with understanding of ML theory, mathematics, and statistical concepts
Experience building, training, validating, and deploying machine learning models
Ability to explain model selection decisions and ML approaches clearly
Strong collaboration and communication skills with the ability to work well across cross-functional teams
Strong personality fit and ability to work effectively in team-oriented environments
Willingness to work onsite

Job Responsibility

Design, build, and support scalable machine learning and data workflows in cloud environments
Develop and maintain MLOps pipelines using Databricks and MLflow
Track, manage, and deploy machine learning models across environments
Work closely with data scientists, engineers, and business stakeholders to deliver ML-driven solutions
Analyze large datasets and apply machine learning techniques to solve business problems
Support model monitoring, optimization, and continuous improvement initiatives
Collaborate on architecture, best practices, and scalable ML engineering standards

Fulltime

Staff Machine Learning Engineer - Data Intelligence

We're building the platform that makes AI possible across Culture Amp. This is a...

Location

Australia , Melbourne

Salary:

Not provided

Culture Amp

Expiration Date

Until further notice

Requirements

Strong platform engineering fundamentals, with experience building and operating services that other teams depend on
Expertise in Python and experience with ML tooling and infrastructure
Deep experience with large-scale data systems (streaming, batch processing, data lakes)
Proven experience with ML infrastructure: model serving, vector databases, embedding pipelines
Strong understanding of cloud platforms (AWS preferred) and backend architecture
Experience building and optimising RAG and retrieval systems
The communication skills to work across teams and influence technical direction beyond your own team

Job Responsibility

Designing and operating the platform services that power AI features across Culture Amp, including inference pipelines, embedding storage, and retrieval systems
Building a scalable approach to vector search across diverse categories of unstructured data (survey responses, performance feedback, company documents)
Driving MLOps and LLMOps practices across the organisation, including observability, cost management, and reliability
Ensuring AI is used responsibly: implementing guardrails, security controls, and data compliance measures
Partnering with data scientists on the team to productionise models and evaluate new AI capabilities

What we offer

Employee Share Options Program
Programs, coaching, and budgets to help you thrive personally and professionally
Access to external providers for mental wellbeing and coaching support
Monthly Camper Life Allowance
Team budgets dedicated to team building activities and connection
Intentional quarterly wellbeing pauses
Extended year-end breaks
Excellent parental leave and in work support program available from day 1
5 Social Impact Days a year
MacBooks for you to do your best & a work from home office budget

Staff Machine Learning Engineer - Data Intelligence

We're building the platform that makes AI possible across Culture Amp. This is a...

Location

Australia , Sydney

Salary:

Not provided

Culture Amp

Expiration Date

Until further notice

Requirements

Strong platform engineering fundamentals, with experience building and operating services that other teams depend on
Expertise in Python and experience with ML tooling and infrastructure
Deep experience with large-scale data systems (streaming, batch processing, data lakes)
Proven experience with ML infrastructure: model serving, vector databases, embedding pipelines
Strong understanding of cloud platforms (AWS preferred) and backend architecture
Experience building and optimising RAG and retrieval systems
The communication skills to work across teams and influence technical direction beyond your own team

Job Responsibility

Designing and operating the platform services that power AI features across Culture Amp, including inference pipelines, embedding storage, and retrieval systems
Building a scalable approach to vector search across diverse categories of unstructured data (survey responses, performance feedback, company documents)
Driving MLOps and LLMOps practices across the organisation, including observability, cost management, and reliability
Ensuring AI is used responsibly: implementing guardrails, security controls, and data compliance measures
Partnering with data scientists on the team to productionise models and evaluate new AI capabilities

What we offer

Employee Share Options Program
Programs, coaching, and budgets to help you thrive personally and professionally
Access to external providers for mental wellbeing and coaching support
Monthly Camper Life Allowance
Team budgets dedicated to team building activities and connection
Intentional quarterly wellbeing pauses
Extended year-end breaks
Excellent parental leave and in work support program available from day 1
5 Social Impact Days a year
MacBooks for you to do your best & a work from home office budget

Manager, Data & Machine Learning Platform Engineer

This Los Angeles-based role is a hands-on opportunity for a Manager, Data & Mach...

Location

United States , Inglewood

Salary:

180000.00 - 200000.00 USD / Year

Robert Half

Expiration Date

Until further notice

Requirements

4+ years of experience in data engineering, machine learning engineering, or MLOps
Proven track record of building end-to-end data and ML systems in production environments
Strong proficiency in Python and SQL
Experience with cloud platforms (Azure, AWS, or GCP) and distributed systems
Expertise in building and maintaining data pipelines (batch and streaming)
Experience deploying ML models into production, including real-time inference systems
Hands-on experience with CI/CD pipelines for ML workflows and containerization tools (e.g., Docker, Kubernetes)
Strong background in designing scalable data models and working with large-scale datasets

Job Responsibility

Design, build, and maintain scalable data pipelines and ML platform infrastructure for analytics and AI use cases
Own the end-to-end lifecycle of data and ML systems, including ingestion, transformation, feature engineering, deployment, and monitoring
Develop and optimize data models and schemas to support both batch and real-time workflows
Build and manage feature pipelines and enable low-latency access for real-time decisioning systems
Deploy machine learning models into production via APIs and real-time inference services
Implement CI/CD pipelines for machine learning workflows, including testing, versioning, and automated deployment
Establish monitoring systems to track data quality, model performance, and system reliability
Enable experimentation frameworks such as A/B testing to support data-driven product iteration
Collaborate cross-functionally with data scientists, product teams, and business stakeholders to deliver impactful AI solutions
Drive architectural decisions and promote best practices in data engineering and MLOps

What we offer

Comprehensive benefits package including medical, dental, and vision coverage
401(k) with company contribution
Annual wellbeing allowance
Flexible paid time off and parental leave
Company-paid life and disability insurance
Mental health and wellness support programs
Flexible spending accounts and family planning assistance

Fulltime

New

Machine Learning Engineer

We are Woolworths Group. Woolworths Group is an Australian food and everyday nee...

Location

Australia , Sydney

Salary:

Not provided

Woolworths Supermarkets

Expiration Date

Until further notice

Requirements

Bachelor's degree or above in Computer Science, Engineering, or a related field
3+ years of commercial software development experience
2+ years of hands-on experience in Python, SQL, and Linux
Hands-on experience with manipulating and processing large, complex datasets (preferred)
Hands-on experience with social media statistics/metrics APIs/tools (preferred)
Hands-on experience with containerized solutions such as Docker (preferred)
Hands-on experience with GenAI(LLM) solutions (preferred)
Experience building Machine Learning / Data pipelines (preferred)
Experience building RESTful APIs (preferred)
Experience in ML Engineering, MLOps, or DevOps (preferred)

Job Responsibility

Design, develop, implement, scale and maintain Advanced Analytics Solutions
Design, develop, implement, scale and maintain Advanced Analytics solutions using predominantly Google Cloud (GCP) products
Develop Cloud based ML pipelines to solve a broad range of business problems
Grow the Engineering Guild capability through pioneering new tech and approaches to improve time to market, reliability and performance of Data Science applications
Work collaboratively with Data Scientists, ML Engineers & Data Engineers to develop cutting edge retail tools in an agile manner
Create, present and seek inputs and feedback on architecture, solution designs and foster alignment and support for solutions
Apply relevant testing frameworks to ensure the robustness of solutions
Communicate analyses, insights, solution designs and showcase working solutions

What we offer

Team discounts across our range of Woolworths Group brands
12 weeks paid parental leave for primary caregivers plus paid superannuation for up to 12 months while the Team Member is on parental leave - eligible from the first day of employment
24/7 access to the Sonder app

Fulltime

New

Principal Machine Learning Engineer - Forecasting

We are seeking a Principal Machine Learning Engineer to join the Forecasting tea...

Location

India , Hyderabad

Salary:

Not provided

Amgen

Expiration Date

Until further notice

Requirements

Degree and 12+ years of experience in machine learning engineering, software engineering, data science engineering, or a related quantitative discipline.
10+ years of professional experience building, deploying, and operating production ML, AI, data, or software systems, including significant experience as a technical lead on complex, cross-functional initiatives.
Demonstrated track record of designing or architecting new and existing systems with emphasis on reliability, scale, security, maintainability, and operational excellence.
Deep hands-on experience with the full ML engineering lifecycle, including data pipelines, feature engineering, experimentation, model training, model integration, testing, deployment, monitoring, evaluation, observability, and continuous improvement.
Strong experience deploying forecasting, probabilistic, Bayesian, predictive, NLP, deep learning, or LLM-based systems in production environments.
Experience building or integrating AI systems, including LLM-powered applications, agentic workflows, retrieval or information-retrieval systems, evaluation frameworks, and human-in-the-loop review patterns.
Strong object-oriented programming skills in Python and SQL, with experience using modern ML and software development frameworks such as scikit-learn, PyTorch, TensorFlow/JAX, Spark, Ray, MLflow, Airflow/Prefect/Dagster, FastAPI, or equivalent technologies.
Experience with cloud platforms and distributed systems, including containerization, CI/CD, infrastructure-as-code, model serving, workflow orchestration, batch and streaming data processing, and production support.
Strong software engineering fundamentals, including system design, architecture trade-off analysis, testing strategies, code reviews, source control, build and release processes, performance optimization, and maintainability.
Demonstrated ability to communicate technical strategy, system tradeoffs, and delivery risks to technical and non-technical stakeholders, including senior leaders, product/program owners, scientists, and business partners.

Job Responsibility

Define and drive the technical strategy for enterprise forecasting and AI decision systems, aligning architecture, reusable platforms, and delivery roadmaps to Amgen's planning, supply, commercial, manufacturing, operations, and patient-focused priorities.
Partner with data scientists, product and program leaders, operations, commercial, manufacturing, supply chain, finance, and other business stakeholders to translate ambiguous requirements into shipped software and measurable business outcomes.
Architect, build, and scale production ML, LLM, and agentic AI systems that combine forecasting, predictive analytics, simulation, optimization, and autonomous or semi-autonomous workflow automation.
Productionize advanced statistical, Bayesian, deep learning, and machine learning models, including training, validation, inference, serving, evaluation, lifecycle management, and governed deployment.
Lead development of AI agent components that automate complex forecasting and operational workflows across multiple systems, decision points, datasets, and user groups while preserving appropriate human-in-the-loop review and escalation patterns.
Design secure integrations across enterprise APIs, databases, analytics platforms, workflow systems, cloud services, and AI orchestration patterns to enable multi-system decision support and scalable automation.
Establish robust MLOps and AI engineering capabilities, including model versioning, CI/CD, automated retraining, performance monitoring, observability, drift detection, service-level reliability, rollback strategies, and operational runbooks.
Implement guardrails, model and agent evaluation frameworks, auditability, explainability, responsible AI controls, and human-in-the-loop operating models for production AI systems in high-impact and regulated business contexts.
Research and evaluate state-of-the-art open-source, vendor, and internal tools related to forecasting, LLMs, AI agents, MLOps, model optimization, model serving, and scalable AI infrastructure for potential application to Amgen business problems.
Provide principal-level technical mentorship, design review leadership, and engineering standard-setting across teams, promoting code quality, documentation, reproducibility, testing, security, privacy, maintainability, and operational excellence.

Fulltime

New

Senior Machine Learning Engineer

Senior Machine Learning Engineer at Amgen. Join Amgen’s Mission of Serving Patie...

Location

United States , Thousand Oaks; Jacksonville

Salary:

156190.05 - 211315.95 USD / Year

Amgen

Expiration Date

Until further notice

Requirements

Solid foundation in machine learning algorithms and techniques
Experience in MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow)
Experience in DevOps tools (e.g., Docker, Kubernetes, CI/CD)
Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn)
Outstanding analytical and problem-solving skills
Ability to learn quickly
Good communication and interpersonal skills
Doctorate degree OR Master’s degree and 2 years of Computer Science experience OR Bachelor’s degree and 4 years of Computer Science experience OR Associate’s degree and 8 years of Computer Science experience OR High school diploma / GED and 10 years of Computer Science experience
Excellent analytical and troubleshooting skills
Strong verbal and written communication skills

Job Responsibility

Collaborate with data scientists to develop, train, and evaluate machine learning models
Build and maintain MLOps pipelines, including data ingestion, feature engineering, model training, deployment, and monitoring
Leverage cloud platforms (AWS, GCP, Azure) for ML model development, training, and deployment
Implement DevOps/MLOps best practices to automate ML workflows and improve efficiency
Develop and implement monitoring systems to track model performance and identify issues
Conduct A/B testing and experimentation to optimize model performance
Work closely with data scientists, engineers, and product teams to deliver ML solutions
Stay updated with the latest trends and advancements

What we offer

A comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions, group medical, dental and vision coverage, life and disability insurance, and flexible spending accounts
A discretionary annual bonus program, or for field sales representatives, a sales-based incentive plan
Stock-based long-term incentives
Award-winning time-off plans
Flexible work models, including remote and hybrid work arrangements, where possible

Fulltime

AI Machine Learning Scientist

Location

United States of America , INDIANAPOLIS

Salary:

Not provided

Elevance Health

Expiration Date

July 15, 2026

Requirements

Bachelor’s degree in a highly quantitative field: Computer Science, Machine Learning, Operational Research, Analytics, Statistics, Mathematics, or a related field of study
Four (4) years of Information Technology (IT) experience, or related experience
Experience with Machine Learning techniques including supervised learning (linear regression and classification) and unsupervised learning (clustering)
Experience with Deep Learning techniques including convolutional neural networks, recurrent neural networks, and reinforcement learning
Experience using Python programming language
Experience with big data technologies including Hadoop, Apache Spark, and AWS
Experience with relational database management and SQL
Experience with Natural Language Processing (NLP) techniques including sentiment analysis and text classification
Experience with statistical analysis and application of statistical methods
Employer will accept a Master’s degree in a highly quantitative field: Computer Science, Machine Learning, Operational Research, Analytics, Statistics, Mathematics, or a related field of study and Two (2) years of Information Technology (IT) experience, or related. Must have the skills listed above.

Job Responsibility

Leverage Artificial Intelligence (AI) scientific and statistical methods to assist with product creation, development, and improvement
Engage with product teams and business stakeholders to align on project objectives and ensure AI models meet business goals
Lead initiatives for developing Machine Learning (ML), Natural Language Processing (NLP), and Large Language Models (LLM) LLM models
Play a critical role in steering the strategic direction for ML, NLP, LLM, and algorithm development within the company’s AI/ML team, collaborating with distinguished experts in AI/ML modeling, ML engineering, data science, and data engineering
Define and articulate roadmaps for AI/ML model development, acting as a key figure in AI-driven transformation to deliver value internally and to customers
Design and develop customized ML, GenAI, NLP, and LLM models for both batch and stream processing-based AI/ML pipelines. This includes handling data ingestion, preprocessing, search and retrieval, Retrieval Augmented Generation (RAG), and ensuring that complete solutions meet all technical and business requirements, as well as Service Level Agreement (SLA) specifications
Work closely with MLOps, machine learning engineers, and software engineers to ensure seamless integration of machine learning models into production systems
Collaborate with the MLOps team to create and maintain strong evaluation solutions and tools that assess model performance, accuracy, consistency, and reliability during development and UAT
Mentor junior team members and influence the strategic direction of our ML and data science projects.

What we offer

merit increases
paid holidays
Paid Time Off
incentive bonus programs
medical
dental
vision
short and long term disability benefits
401(k) +match
stock purchase plan

Fulltime

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Data Engineer / Data Scientist – MLOps & Machine Learning

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