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Nesting Engineer Jobs in McLean, VA (NOW HIRING)

Web Developer Master Work Arrangement: Onsite Worksite Address: Washington, DC Interviews: In ... Nice to Have ◦ Strong SCSS/SASS skills: nesting, mixins, functions, partials, and a disciplined ...

Web Developer Master

Washington, DC · On-site

$90 - $130/hr

Web Developer Master Work Arrangement: Onsite Worksite Address: Washington, DC Interviews: In ... Strong SCSS/SASS skills: nesting, mixins, functions, partials, and a disciplined file architecture.

Candidates may be asked to survey for rare plants, conduct nest surveys, cover for environmental ... project, including clients, engineers, stakeholders, government personnel, land owners ...

Showing results 41-60

Nesting Engineer information

See McLean, VA salary details

$39.4K

$102.9K

$139K

How much do nesting engineer jobs pay per year?

As of Sep 6, 2026, the average yearly pay for nesting engineer in McLean, VA is $102,857.00, according to ZipRecruiter salary data. Most workers in this role earn between $84,900.00 and $117,800.00 per year, depending on experience, location, and employer.

What is a nesting engineer?

A Nesting Engineer is responsible for optimizing the arrangement of parts on raw materials, such as metal sheets, to minimize waste and improve manufacturing efficiency. They use specialized CAD/CAM software to generate cutting patterns for CNC machines. This role requires knowledge of manufacturing processes, material properties, and cost optimization. Nesting Engineers work closely with production teams to ensure accuracy and efficiency in fabrication.

What are the typical daily responsibilities of a nesting engineer?

Nesting Engineers spend their days preparing and optimizing cutting patterns for sheet metal or other raw materials using advanced CAD/CAM and nesting software. They collaborate closely with production planners, machine operators, and quality assurance teams to ensure that designs are not only efficient but also manufacturable to required specifications. Regular tasks include analyzing job orders, updating project files, troubleshooting design issues, and making real-time adjustments for manufacturing constraints. This role involves both independent technical work and active communication with various departments to keep production running smoothly.

What are the key skills and qualifications needed to thrive in the nesting engineer position, and why are they important?

A successful Nesting Engineer needs a strong background in mechanical engineering, CAD/CAM software proficiency, and a solid understanding of manufacturing processes and materials. Familiarity with specialized nesting software such as SigmaNEST, AutoCAD, or TruTops, and often certifications in CAD or sheet metal fabrication are typically required. Attention to detail, excellent problem-solving skills, and effective teamwork abilities help Nesting Engineers excel in optimizing production layouts. These skills ensure efficient material usage, minimize waste, and contribute to streamlined manufacturing operations.

What cities near McLean, VA are hiring for Nesting Engineer jobs?

Cities near McLean, VA with the most Nesting Engineer job openings:

Infographic showing various Nesting Engineer job openings in McLean, VA as of August 2026, with employment types broken down into 82% Full Time, 12% Part Time, and 6% Contract. Highlights an 100% In-person job distribution, with an average salary of $102,857 per year, or $49.5 per hour.

Senior SAS/Python Programmer

Econometrica, Inc.

Bethesda, MD • On-site, Remote

Full-time

Medical, Dental, Vision, Retirement

Posted 9 days ago


Job description

About Econometrica, Inc. Econometrica, Inc., is a research and management organization committed to providing high-quality, cost-effective economic and analytical services for clients in the private and public sectors. Since its founding in 1998, Econometrica has been involved in complex, high-profile contracts for numerous Federal departments and agencies in the healthcare, education, transportation, energy, housing, and finance sectors

Econometrica specializes in research, econometric, analytical, and technical support for our clients, with an emphasis on data science, data analytics, statistics, economic analyses, and program implementation and evaluation services. The Opportunity Econometrica is seeking a Senior Programmer to lead the AI-assisted conversion of large legacy SAS codebases into modern SQL- and Python-based cloud computing environments. This is a hands-on engineering role for someone who is genuinely fluent in both languages: the ideal candidate can read a 3,000-line SAS macro with nested %DO loops, PROC SQL pass-through, and multi-level formats and understand what the equivalent, maintainable Python or SQL implementation should look like.

The selected candidate will use large language models (LLMs) and generative AI tooling as a force multiplier - not as a black box. A central responsibility of this role is designing the workflow that makes AI-assisted conversion trustworthy: decomposing legacy code into translatable units, engineering prompts and context that produce correct output, and building the automated validation harnesses that prove the converted code reproduces the original results to the row and to the decimal. The candidate will work alongside a multidisciplinary team of statistical programmers, data engineers, data scientists, and client stakeholders, and will help establish the conversion patterns, standards, and documentation that subsequent modernization projects reuse.

Tasks may include the following: Assessing and inventorying existing SAS code bases-including DATA steps, PROC SQL, macros, arrays, formats, and complex conditional logic-to determine business logic, data lineage, dependencies, and modernization priorities. Designing, prompting, and iterating on LLM-based conversion workflows to re-engineer SAS programs for Python- and SQL-based cloud environments while avoiding literal "SAS-in-Python" anti-patterns and applying appropriate performance optimizations. Building and running equivalence-testing harnesses that compare legacy SAS output against converted output at scale - row counts, key-level joins, column-by-column value comparison with defined numeric tolerances, distributional checks, and edge-case handling - and documenting every accepted discrepancy with its justification.

Refactoring machine-generated code into production-quality, modular pipelines in modern cloud environments, which may include Azure or AWS, and coordinating with the Data Engineering team on orchestration, scheduling, and deployment. Identifying data quality issues surfaced during conversion and developing recommendations on how to resolve them to ensure data completeness, consistency, and accuracy for clients' analytical products. Documenting conversion methodology, mapping logic, validation evidence, and residual risk in a form suitable for client acceptance, audit, and recordkeeping requirements - and preparing plain-language summaries for nontechnical audiences.

Mentoring junior SAS and Python programmers on modernization techniques and on the responsible, verified use of AI coding assistants. Education and Qualifications Required Skills and Experience: Five (5) or more years of hands-on experience using SAS for data analytics and reporting. Three (3) or more years of hands-on experience manipulating data in Python, with required proficiency in Pandas.

Three (2) or more years of hands-on experience working in a modern cloud environment (Azure, AWS, or GCP). Two (2) or more years of hands-on experience conducting advanced data analysis in SQL. Ability to independently investigate and lead to completion programming tasks of high complexity, and to independently conduct quality assurance and troubleshoot coding issues.

Ability to work effectively in a multidisciplinary team setting and to develop effective relationships with clients, consultants, and contractors. Ability to obtain and maintain public trust security clearance. Desired Skills and Experience: SAS Base and Advanced certifications.

Certifications in cloud architecture, data engineering, or related disciplines. Demonstrated experience converting, refactoring, or re-platforming legacy analytic code, with a documented approach to validating that modernized outputs match legacy results. Experience with version control (Git) and collaborative development workflows, including code review and documentation.

Experience with distributed processing frameworks (e.g., Spark/PySpark) for large-scale data transformation. Additional requirements for the position could involve occasional travel relevant to the responsibilities noted above. Education Master's or doctorate-level degree in data science, computer science, mathematics, or a related field; OR ten (10) years of applied work experience in one of the same fields

Our Generous Benefits Package Includes: Being part of a dynamic research group that continues to grow. Company-sponsored healthcare plan and optional vision/dental coverage. Excellent training and development opportunities.

Referral bonuses. 401(k) program. Organized social activities.

Metro SmartBenefits Program. Work Environment This position is remote, though candidates may choose to work in Econometrica's office if they are local. The office is located at a Metro stop in beautiful downtown Bethesda, MD, within walking distance of great restaurants and local fare.

We have a typical office setting with a quiet-to-moderate noise level. Physical Requirements The physical requirements are representative of those an employee encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

The above job description is not intended to be an all-inclusive list of duties and standards of the position. Other instructions and related duties may be assigned by the employee's supervisor. Econometrica, Inc., is an Equal Opportunity Employer (EOE), and we seek to create an inclusive workplace that embraces diverse backgrounds, life experiences, and perspectives.