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Entry Level Apple Machine Learning Engineer Jobs in Duson, LA

First Solar

Technician- Automation I USA

New Iberia, LA · On-site

$32K/yr

The following is an entry level Automation Technician controls position where a successful ... programming/trouble-shooting Rockwell Automation Human Machine Interfaces (HMI) utilizing ...

Marmon

Blaster

Ville Platte, LA

$13 - $17.25/hr

General Labor, Machine Operator, Maker/Packer, Assembler and Line Operator. Assembles minor ... Union Tank Car Company's regulatory, engineering, and commercialexpertisemake UTLX the preferred ...

Marmon Holdings, Inc.

Blaster

Ville Platte, LA · On-site

$13 - $17.25/hr

General Labor, Machine Operator, Maker/Packer, Assembler and Line Operator. Assembles minor ... Union Tank Car Company's regulatory, engineering, and commercial expertise make UTLX the preferred ...

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All JobsApple Machine Learning Engineer JobsEntry Level Apple Machine Learning Engineer JobsEntry Level Apple Machine Learning Engineer Jobs in Duson, LA

Entry Level Apple Machine Learning Engineer information

See Duson, LA salary details

$27.5K

$63.6K

$108.3K

How much do entry level apple machine learning engineer jobs pay per year?

As of Jul 13, 2026, the average yearly pay for entry level apple machine learning engineer in Duson, LA is $63,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $47,300.00 and $72,000.00 per year, depending on experience, location, and employer.

What does an Entry Level Apple Machine Learning Engineer do?

An Entry Level Apple Machine Learning Engineer helps design, develop, and implement machine learning models and algorithms for Apple products and services. They work closely with senior engineers and data scientists to collect and analyze data, build prototypes, and improve the performance of machine learning systems. Responsibilities often include coding, model evaluation, and collaborating with cross-functional teams to integrate ML solutions into Apple’s ecosystem. This role is ideal for those with a strong foundation in programming, statistics, and a passion for innovative technology.

What is the difference between Entry Level Apple Machine Learning Engineer vs Entry Level Data Scientist?

AspectEntry Level Apple Machine Learning EngineerEntry Level Data Scientist
Required CredentialsBachelor's in CS, ML, or related; knowledge of ML frameworksBachelor's in CS, Statistics, or related; strong analytical skills
Work EnvironmentTech company, R&D, product developmentData analysis, research, business insights
Employer & Industry UsageApple, consumer electronics, softwareVarious industries including tech, finance, healthcare
Common Search & ComparisonYesYes

Entry Level Apple Machine Learning Engineers focus on developing ML models for Apple products, requiring knowledge of ML frameworks and programming. Entry Level Data Scientists analyze data to derive insights, often with statistical expertise. While both roles involve data and programming, ML Engineers emphasize model deployment, whereas Data Scientists focus on data analysis and reporting.

What are the key skills and qualifications needed to thrive as an Entry Level Apple Machine Learning Engineer, and why are they important?

To thrive as an Entry Level Apple Machine Learning Engineer, you generally need a solid background in computer science, mathematics, and statistics, often supported by a relevant degree and coursework in machine learning. Familiarity with programming languages such as Python or Swift, experience with machine learning frameworks like TensorFlow or PyTorch, and knowledge of Apple's development tools like Core ML are typically required. Strong problem-solving abilities, teamwork, and effective communication skills help you collaborate and contribute innovative solutions in a dynamic tech environment. These competencies are crucial for developing and optimizing machine learning models that power Apple's products and services.

What are some common challenges faced by entry-level Machine Learning Engineers at Apple, and how can they overcome them?

Entry-level Machine Learning Engineers at Apple often encounter challenges such as adapting to the company's fast-paced innovation cycle, understanding large and complex codebases, and collaborating with cross-functional teams. To overcome these hurdles, it's important to proactively seek mentorship, participate in code reviews, and familiarize oneself with Apple's internal tools and documentation. Regular communication with peers and senior engineers can also help accelerate the learning curve and foster a collaborative environment that encourages innovation and knowledge sharing.
Entry Level Apple Machine Learning Engineer jobs near you

Data Scientist-Direct Hire-6-Month Register

Criminal Investigation & Law Enforcement | IRS Careers

Lafayette, LA

$125K/yr

Other

Posted 13 days ago

Job description

WHAT IS DATA AND ANALYTICS (DA)-RESEARCH APPLIED ANALYTICS & STATISTICS (RAAS)?

A description of the business units can be found at: https://www.jobs.irs.gov/about/who/business-divisions

  • Position(s) are to be filled in the following area(s):
    • DAO DATA AND ANALYTICS
  • Consider each location carefully when applying. If you are selected for a location, that location will become your official post of duty.
REVIEW THE ADDITIONAL INFORMATION BELOW FOR FURTHER DETAILSQualifications:Federal experience is not required. Experience may have been gained in the public sector, private sector or through Volunteer Service. One year of experience refers to full-time work; part-timework is considered on a prorated basis. To ensure full credit for your work experience, please indicate dates of employment by month/day/year, and indicate number of hours worked per week, on your resume.
You must meet the following requirements by the cut-off dates as shown in announcement under the 'How to Apply' section.
QUALIFICATION REQUIRMENTS: BASIC REQUIREMENTS All GRADES: EDUCATION:
You must have a bachelor's or higher degree in mathematics, statistics, computer science, data science or other field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
OR
COMBINATION OF EDUCATION AND EXPERIENCE: A combination of education and experience that includes courses equivalent to a major field of study (30 semester hours) as shown in the paragraph above, plus additional education or appropriate experience.
AND
SPECIALIZED EXPERIENCE GRADE 14: In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-13 grade level in the Federal service. Specialized experience for this position includes experience performing all the following:
  • Leading data science or statistical analysis initiatives by defining project scope, analytic approach, data requirements, schedules, deliverables, or success measures; coordinating work across data, program, business, or technology stakeholders; and developing findings or recommendations for program or operational decisions.
  • Developing or applying statistical, machine learning, operations research, artificial intelligence, or other data science methods to evaluate programs, operations, compliance, or organizational performance, for example forecasting, predictive or prescriptive modeling, optimization, natural language processing or text analytics, graph or link analysis, neural networks or deep learning, or exploratory data analysis.
  • Overseeing data preparation, data quality, data governance, data certification, or analytic product delivery using programming, query, scripting, or analytic tools, such as Structured Query Language (SQL), R, Python, SAS, or equivalent tools, to support reproducible analysis, reporting, modeling, or decision-support products.
  • Experience manipulating datasets in relational databases (e.g., Compliance Data Warehouse, Enterprise Data Platform).
  • Advising managers or senior leaders on data science findings, automation opportunities, policy or program impacts, resource implications, risks, or recommended changes to processes, procedures, or operations.
  • Providing technical guidance, review, or mentoring to analysts or data scientists and preparing technical reports, briefings, presentations, or documentation that explain methods, assumptions, limitations, validation results, success measures, key performance indicators, or recommendations.
AND
You must also meet the following requirements:
  • MINIMUM AGE REQUIREMENT: Minimum age for federal employment is 18 years old, or at least 16 years old and have:
    • Graduated from high school or been awarded a certificate equivalent to graduating from high school; or
    • Completed a formal vocational training program; or
    • Received a statement from school authorities agreeing with your preference for employment rather than continuing your education
For more information on qualifications please refer to OPM's Qualifications Standards.Education:A college or university degree generally must be from an accredited (or pre-accredited) college or university recognized by the U.S. Department of Education. For a list of schools which meet these criteria, please refer to Department of Education Accreditation page.
FOREIGN EDUCATION: Education completed in foreign colleges or universities may be used to meet the requirements. You must show proof the education credentials have been deemed to be at least equivalent to that gained in conventional U.S. education program. It is your responsibility to provide such evidence when applying. Click here (Section 3, Explanation of Terms) or here for Foreign Education Credentialing instructions.
We recommend choosing an evaluator from a member organization of one of the following national associations of credential evaluation services: National Association of Credential Evaluation Services (NACES) or Association of International Credentials Evaluators (AICE).Employment Type: OTHER

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