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Remote Machine Learning Jobs in Crown Point, IN (NOW HIRING)

Contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and ... full-stack, machine learning, and other engineers -- who are driving real-world impact in AI ...

Contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and ... full-stack, machine learning, and other engineers -- who are driving real-world impact in AI ...

Data Solutions Engineer

Chicago, IL · On-site +1

$91K - $156K/yr

Stay abreast of the latest trends in cloud computing, machine learning, AI, and data engineering. Explore new technologies and methodologies to continuously improve systems, tools, and data processes.

Vision Engineer - Remote / Travel DISHER is currently partnering with a world leading automation ... Knowledge on machine learning with AI capabilities. * Self-driven and willingness to work long ...

Vision Engineer - Remote / Travel DISHER is currently partnering with a world leading automation ... Knowledge on machine learning with AI capabilities. * Self-driven and willingness to work long ...

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Remote Machine Learning information

See Crown Point, IN salary details

$24.2K

$40.4K

$83.5K

How much do remote machine learning jobs pay per year?

As of Jul 14, 2026, the average yearly pay for remote machine learning in Crown Point, IN is $40,405.00, according to ZipRecruiter salary data. Most workers in this role earn between $30,800.00 and $43,600.00 per year, depending on experience, location, and employer.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data modeling, and often working at large tech companies or in specialized industries can earn salaries approaching or exceeding $500,000 annually. Compensation may include base salary, bonuses, and stock options, especially in high-demand markets.

What are the key skills and qualifications needed to thrive as a Remote Machine Learning Engineer, and why are they important?

To thrive as a Remote Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (often Python), and experience with machine learning frameworks, typically supported by a relevant degree. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (like AWS or GCP), and version control systems is crucial. Strong problem-solving abilities, self-management, and effective virtual communication distinguish top performers in remote settings. These competencies ensure the engineer can build effective models, collaborate across distributed teams, and deliver impactful solutions independently.

How to make 2000 a week working from home?

Remote machine learning professionals can earn $2,000 or more weekly by taking on high-paying freelance projects, consulting roles, or working for companies that offer remote positions with competitive salaries. Building specialized skills in programming, data analysis, and tools like Python, TensorFlow, or cloud platforms can increase earning potential. Consistent work, a strong portfolio, and networking are key to reaching this income level from home.

What Are Remote Machine Learning Jobs?

Machine learning is a method of analyzing data via automating analytical model building. The premise is that systems can learn from data. Machine learning positions include machine learning engineer, computer vision engineer, and senior deep learning engineer. In a remote machine learning job, you work from home in a branch of artificial intelligence performing duties related to computational processing and data. Your goal is to design models that solve business problems, such as helping organizations avoid unknown risks or find profitable opportunities. Your responsibilities include maintaining data pipelines, performing model research and implementation, building machine learning systems, and onboarding new utilities.

What is a remote machine learning job?

A remote machine learning job involves working with algorithms, data, and models to develop predictive systems or automate tasks, all while working from a location outside of a traditional office setting. Professionals in this role use techniques from statistics and computer science to analyze data, train machine learning models, and deploy solutions for real-world applications. Remote machine learning jobs can span various industries, including technology, healthcare, finance, and e-commerce. These roles typically require strong programming skills, knowledge of machine learning frameworks, and the ability to communicate findings effectively with team members or stakeholders. Working remotely offers flexibility, but also requires discipline and self-motivation to succeed.

What are some effective strategies for collaborating with team members while working remotely as a Machine Learning Engineer?

Collaboration in a remote Machine Learning role often relies on clear communication through digital tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular check-ins and stand-up meetings help keep everyone aligned on project goals and timelines. Sharing code and models via version control systems (like Git) and using collaborative notebooks (such as JupyterHub or Google Colab) are also common practices. Building strong documentation habits and proactively seeking feedback can help ensure smooth teamwork and project success, even across different time zones.

What is the difference between Remote Machine Learning vs Data Scientist?

AspectRemote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML certificationsBachelor's/Master's in CS, Statistics, or related field
Work EnvironmentRemote, collaborative teams, tech companiesRemote or on-site, diverse industries, analytics focus
Industry UsageTech, AI startups, researchFinance, healthcare, e-commerce, tech
Search & Comparison IntentOften compared for technical roles in AI/MLBroader data analysis roles, but overlapping skills

Remote Machine Learning specialists focus on developing algorithms and models primarily in tech environments, often requiring advanced programming and ML knowledge. Data Scientists analyze data to extract insights, sometimes utilizing ML techniques. While both roles share skills and credentials, Remote Machine Learning emphasizes model development, whereas Data Scientists focus on data analysis and interpretation.

Are there remote machine learning jobs?

Yes, remote machine learning jobs are widely available across various industries, often requiring skills in programming, data analysis, and familiarity with tools like Python, TensorFlow, or PyTorch. Many companies offer flexible schedules and remote work options for qualified candidates, especially in tech and research sectors.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and deploy AI models, and their role involves understanding algorithms, data preprocessing, and model optimization. While AI automation tools can handle certain tasks, MLEs are essential for creating, fine-tuning, and maintaining complex AI systems, making complete replacement unlikely in the near term.
What job categories do people searching Remote Machine Learning jobs in Crown Point, IN look for? The top searched job categories for Remote Machine Learning jobs in Crown Point, IN are:
What cities near Crown Point, IN are hiring for Remote Machine Learning jobs? Cities near Crown Point, IN with the most Remote Machine Learning job openings:
Infographic showing various Remote Machine Learning job openings in Crown Point, IN as of July 2026, with employment types broken down into 1% As Needed, 72% Full Time, 24% Part Time, 1% Temporary, 1% Contract, and 1% Nights. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $40,405 per year, or $19.4 per hour.
Staff Software Engineer | Semantic Data Lake

Staff Software Engineer | Semantic Data Lake

WEX

Chicago, IL • Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 3 days ago


WEX Inc. rating

7.3

Company rating: 7.3 out of 10

Based on 21 frontline employees who took The Breakroom Quiz

14th of 20 rated payment service providers


Job description

This is a remote position; however, the candidate must reside within 30 miles of one of the following locations: Portland, ME; Boston, MA; Chicago, IL; San Francisco Bay Area, CA; and Seattle/WA.

About the Team/Role

WEX is reimagining its enterprise data platform with a powerful goal: transforming raw data into semantically meaningful, reusable, and trusted business assets. As a Staff Software Engineer on the Semantic Data Lake Team, you'll play a critical role in designing, building, and maintaining our core 360 data objects-such as Customer360, Fleet360, and Provider360.

These wide, entity-based tables are foundational to our analytics, AI, and product platforms. You'll implement rich transformation logic, encode business rules, and ensure data consistency across domains, making our data models both technically scalable and business-ready.

This team is at the heart of WEX's DaaS platform-bridging raw data with meaningful business insights. You'll help define and deliver the semantic backbone of our products, analytics, and machine learning systems.

We're looking for an AI-native engineer: someone who builds with modern AI coding tools (Claude, Copilot, Cursor, and similar) and Spec-Driven Development (SDD) as a core part of their daily workflow, not an occasional add-on. You'll use these tools to accelerate design, generate and refactor transformation logic, write tests, document semantics, and explore data-while applying the engineering judgment needed to ship production-grade, trustworthy data assets.

If you're excited about building semantic models that carry real-world meaning, scale to billions of records, and unify how a business understands its world-and doing it with the leverage of modern AI tooling-this is your next big move.

How you'll make an impact
  • Design and implement semantically consistent, scalable 360 data models that integrate data across domains.

  • Build and maintain transformation pipelines that apply cleansing, standardization, enrichment, and derived logic to domain datasets.

  • Write production-quality, testable code in SQL and Python (or equivalent)-delivering performant and maintainable data assets.

  • Leverage AI coding assistants (Claude, Copilot, Cursor, and similar) to accelerate development-drafting transformation logic, generating tests, refactoring pipelines, exploring datasets, and producing semantic documentation-while critically reviewing AI output for correctness, performance, and alignment with business rules.

  • Develop and share patterns, prompts, and workflows that help the team get more leverage out of AI tooling, raising the bar for AI-native engineering practices across the Semantic Data Team.

  • Work closely with domain experts, data scientists, and product stakeholders to translate business concepts into interpretable, decision-ready data models.

  • Implement logic for classifications, KPIs, scoring algorithms, and business rules, ensuring traceability and data lineage.

  • Help define and enforce standards for data modeling, documentation, and governance within the semantic layer-including standards for responsible, auditable use of AI-generated code and artifacts.

  • Collaborate across teams to integrate with ingestion, MDM, and data product layers, and explore opportunities to expose 360 objects to LLM-powered and agentic applications.

Experience you'll bring
  • 8+ years of experience in data engineering or software engineering with a focus on data transformation, modeling, or analytics platforms.

  • Strong proficiency in SQL and at least one general-purpose language such as Python or Scala.

  • Demonstrated experience as an AI-native engineer-using tools like Claude, GitHub Copilot, Cursor, or similar as part of your everyday development workflow, with a clear point of view on where they accelerate your work and where human judgment is essential.

  • Comfort with modern AI engineering practices such as prompt design, context engineering, Spec-Driven Development (SDD), AI-assisted code review, and integrating LLMs or AI agents into engineering or data workflows.

  • Experience building and scaling wide, entity-based tables and modeling domain concepts (e.g., customer, fleet, provider) into durable data objects.

  • Solid understanding of data quality practices-including validation, enrichment, schema enforcement, and business rule encoding.

  • Experience working with large-scale datasets and optimizing transformation pipelines for performance and maintainability.

  • Comfort operating in a collaborative, cross-functional environment, balancing business logic with platform scalability.

  • A mindset for traceability, reproducibility, and semantic clarity-you build data models others (humans and AI systems alike) can trust and reuse.

Bachelor's degree in Computer Science, Software Engineering, or related field. A Master's or PhD in Data Science, Machine Learning, Artificial Intelligence, Computer Science, or Statistics is a big plus.

    The base pay range represents the anticipated low and high end of the pay range for this position. Actual pay rates will vary and will be based on various factors, such as your qualifications, skills, competencies, and proficiency for the role. Base pay is one component of WEX's total compensation package. Most sales positions are eligible for commission under the terms of an applicable plan. Non-sales roles are typically eligible for a quarterly or annual bonus based on their role and applicable plan. WEX's comprehensive and market competitive benefits are designed to support your personal and professional well-being. Benefits include health, dental and vision insurances, retirement savings plan, paid time off, health savings account, flexible spending accounts, life insurance, disability insurance, tuition reimbursement, and more. For more information, check out the "About Us" section.Pay Range: $140,600.00 - $173,100.00

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