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Freelance Machine Learning Data Annotation Jobs in Michigan

Mariana Minerals

Machine Learning Engineer

Ann Arbor, MI · On-site

$120K - $160K/yr

... data-driven decision-making. The Role Mariana Minerals is building the critical minerals supply ... As a Machine Learning Engineer at Mariana, you'll help build and improve the machine learning ...

Stefanini

Machine Learning Engineer

Dearborn, MI

Stefanini is looking for a Machine Learning Engineer, Dearborn, MI (Onsite) For quick apply, please ... Big Data - Experience working with large-scale data processing frameworks such as Apache Spark ...

AceStack LLC

Robotics Data Engineer

Warren, MI

$107K - $128K/yr

Warren, MI FTE • 3+ years of experience in data engineering, machine learning systems, robotics ... annotation workflows at scale. • Hands-on knowledge of TensorFlow and/or PyTorch from a data ...

FastTek

Machine Learning Engineer

Dearborn, MI

$105K - $126K/yr

Machine Learning Engineer #1054987 * Employees in this job function are responsible for designing ... GCP, Big Data, Artificial Intelligence & Expert Systems, API * GCP - Experience deploying and ...

V2Soft

Machine Learning Engineer

Dearborn, MI · On-site

$105K - $126K/yr

Required : • Python • Machine Learning • Data Science • GCP • Big Query • 6+ years in IT • 4+ years in development • Experience designing and implementing Agentic AI solutions, multi ...

General Motors

Senior AI/ML Engineer

Lansing, MI · On-site +1

$106K - $145K/yr

... machine data labeling tools and pipelines that power autonomous vehicle machine learning models ... data annotation (pre‑labeling, autolabeling, active learning loops), helping us move from ...

Varsity Tutors

Machine Learning Tutor

Kalamazoo, MI · Remote

$40/hr

Guides students through data preprocessing, feature selection, building and comparing ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Ann Arbor, MI · Remote

$40/hr

Guides students through data preprocessing, feature selection, building and comparing ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Detroit, MI · Remote

$40/hr

Guides students through data preprocessing, feature selection, building and comparing ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Canopy

Senior Machine Learning Engineer

Detroit, MI · On-site

$95K - $131K/yr

Develop within the full machine learning lifecycle; from problem definition to data pipeline design, model development, validation, deployment, and monitoring. * Establish and refine best practices ...

SynergisticIT

AI and Machine Learning Engineer

Detroit, MI

$104K - $125K/yr

Machine Learning And Artificial Intelligence Developer You will be responsible for Machine Learning ... Design Client and Deep AI Models for different types of data (time-series, sales, business data ...

Indeed

Machine Learning Engineer

Detroit, MI

As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain ... Debug data, models, and system issues * Build training, inference, and eval pipelines Skills ...

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All JobsFreelance Machine Learning Data Annotation JobsFreelance Machine Learning Data Annotation Jobs in Michigan

Freelance Machine Learning Data Annotation information

What is the difference between Freelance Machine Learning Data Annotation vs Data Labeler?

AspectFreelance Machine Learning Data AnnotationData Labeler
CredentialsBasic understanding of annotation tools, sometimes with specialized domain knowledgeTypically no formal credentials required
Work EnvironmentRemote, flexible, project-basedOften remote or in-house, depending on employer
Industry UsageUsed in AI/ML development for training datasetsUsed in data preparation for various industries, including AI
Search/Comparison IntentFocuses on freelance opportunities, project scope, and toolsMore general, often employed by companies for data labeling tasks

Freelance Machine Learning Data Annotation involves independently completing annotation tasks for AI models, often with specialized tools and domain knowledge. Data Labelers typically perform similar tasks but may work as employees or contractors within a company. The main difference lies in the freelance nature and project-based work of data annotation roles.

What are the key skills and qualifications needed to thrive as a Freelance Machine Learning Data Annotation specialist, and why are they important?

To thrive as a Freelance Machine Learning Data Annotation specialist, you need attention to detail, basic knowledge of data labeling concepts, and familiarity with machine learning data types. Experience with annotation tools (such as Labelbox, RectLabel, or CVAT) and understanding of data privacy protocols are commonly required. Strong communication, time management, and the ability to follow complex guidelines are essential soft skills for delivering accurate results. These skills ensure high-quality, consistent data annotation, which is critical for effective machine learning model training and performance.

What is freelance machine learning data annotation?

Freelance machine learning data annotation involves labeling or tagging data—such as images, text, audio, or video—to help train machine learning models. As a freelancer, you work independently or through platforms, completing specific annotation tasks assigned by companies or researchers. This work is essential because high-quality labeled data is required for AI systems to learn and make accurate predictions. Annotators may categorize images, transcribe speech, or highlight relevant information in documents. The flexibility of freelancing allows you to choose projects and work remotely.

What are some common challenges faced by freelance machine learning data annotators, and how can they be managed?

Freelance machine learning data annotators often encounter challenges such as maintaining data accuracy, handling repetitive tasks, and understanding complex annotation guidelines. Staying organized and regularly reviewing project instructions can help ensure consistency and quality in annotations. Additionally, communicating proactively with project managers and utilizing annotation tools efficiently can help manage workload and clarify uncertainties. Building expertise in different data types (text, image, audio) also allows annotators to diversify their projects and reduce monotony.
What are popular job titles related to Freelance Machine Learning Data Annotation jobs in Michigan? For Freelance Machine Learning Data Annotation jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Freelance Machine Learning Data Annotation jobs in Michigan look for? The top searched job categories for Freelance Machine Learning Data Annotation jobs in Michigan are:
What cities in Michigan are hiring for Freelance Machine Learning Data Annotation jobs? Cities in Michigan with the most Freelance Machine Learning Data Annotation job openings:
Freelance Machine Learning Data Annotation jobs near you

Machine Learning Engineer (09235)

Talent Management Plus, Inc.

Detroit, MI

$113K - $136K/yr

Other

Posted 23 days ago

Job description

Position: Machine Learning Engineer (09235)
Location: Detroit, MI
Duration: 6 months+
Summary:
The Data Science and Analytics Center of Excellence (COE) is responsible for leading the creation and development of the overall strategy and direction of data science and advanced analytics - including ensuring continuity and seamless extension of existing programs, the development of a short- and long-term vision and roadmap, and defining and institutionalizing the role that data and analytics play throughout the organization as the fuel that drives and shapes client's priorities and serves as an accelerant for client's progress.
Description:
The ML Engineer is a key player in the Integrated Tech Programs & Strategies team. This role will be responsible for data engineering, data science Model deployment, testing and management for the end-to-end ML and data pipeline including data products. This role will leverage Client's AI labs environment to enable the delivery in a common data lake and products.
Responsibilities:
  • Responsible for building and managing end-to-end data pipelines and operations from ingestion and integration through delivery for the data science prototypes and data products.
  • Adept at queries, report writing and presenting findings, analyze large complex datasets to extract insights and decide on the appropriate technique.
  • Understand and use data and ML fundamentals, including data structures, algorithms, computability and complexity and computer architecture.
  • Collaborate with data engineers to build data and model pipelines, manage the infrastructure and data pipelines needed to bring code to production.
  • Provide support to engineers and product managers in implementing machine learning in the product.
  • Drive the design, building and launching of new data models and ML/Data pipelines in production.
  • Identify, analyze, and interpret trends or patterns in complex data sets.
  • Consulting with managers, Product owners to determine and refine machine learning objectives.
  • Transforming data science prototypes and applying appropriate ML tools and technologies.
  • Contribute and support the development of the overall data science and machine learning strategy and roadmap.

Required Skills:
  • Bachelor's degree in computer science, or equivalent IT knowledge/experience.
  • 2+ years of relevant work experience in Data Analysis, Data Engineer, Data Science & Data Integration.
  • Must have strong data infrastructure, data engineering and Machine Learning skills
  • Must have a proven track record of leading and scaling data pipelines, ML Model deployments in a cloud/on prem/big data environment
  • Strong knowledge of and experience with reporting packages (Business Objects etc.), databases (SQL etc.), programming (XML, JavaScript, or ETL frameworks).
  • Programming languages: SQL, Spark, Python, R, Jupyter Notebooks, Java, Scala, C++
  • Data Exploration and ETL: Alteryx, Talend, H2O, Informatica, Data Stage, Azure Data explorer, Azure Data Factory.
  • Data Warehouse Solutions: Redshift, Snowflake, Postgres, Data Lake.
  • Big Data technologies: Azure, AWS, Hadoop, Spark, Hive, Kafka, Flume, NoSQL stores (HBase, Cassandra, DynamoDB, MongoDB).
  • Cloud storage: S3, GCS, ADLS, Blob.
  • Machine Learning: Cloudera Data Science Workbench, Azure ML, Amazon ML, Google AutoML, Vertex AI.
  • Data Visualization Solutions: MS Power BI, Looker, Tableau, Azure Streaming Analytics, Data Lake Analytics, Azure Time Series Insights, Azure Synapse Analytics.
  • CI/CD and Code Management: Git, Maven, Docker, Jenkins, Azure Dev Ops.
  • Experience working with Data engineering, Data science, ETL teams and managing implementing projects that utilize big data, advanced analytics, and machine learning technologies.
  • Hands-on experience in building data and ML pipelines from variety of sources such as data warehouses and in-memory OLAP models, as well as experience in NoSQL/cloud.
  • Strong understanding of data, ML Models, Big Data, Relational databases, streaming and batch data processing.
  • Knowledge of machine learning evaluation metrics and best practice.
  • Strong experience building end-to-end data view with focus on integration.

Preferred Skills:
  • Experience working with on-prem and cloud-based data warehouses
  • Experience with cloud-based personalization and machine-learning applications.
  • Experience working for consumer or business-facing digital brands.

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