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Key statistics

The identity block — every fact is canon, none is generated.

1 of 8

Track

Individual contributor

Family rungs priced

P1 · P2 · P3 · P4 · P5 · P6

17-0000

manufacturing

Coordinates

3 / 4 spaces

pay@2 · 2026-07

What this role is

Entry-level engineer supporting manufacturing process design and improvement under close guidance. At the Entry-Level Professional (P1) level, the role owns own tasks within a defined component, routine problems with known solutions, and drives own deliverables. None — building the craft.

What this level does

Assists in designing and documenting manufacturing processes for existing products under close supervision, following established procedures and detailed instruction
Collects and records process data (cycle times, workflow observations, equipment settings) to support senior engineers' process evaluations
Helps prepare specifications and routings by gathering equipment and material information from catalogs and vendors
Supports cross-functional teams (production, quality, maintenance) by relaying process issues and shadowing troubleshooting on the line
Learns to use CAD/CAM tools and basic statistical methods (e.g., Minitab) to document layouts and summarize process measurements

Knowledge applied: Applies foundational engineering science and math to document and support existing manufacturing processes; learning CAD/CAM and basic statistical tools on the job
Complexity & problem solving: Handles routine, well-defined tasks with standard answers under detailed instruction
Collaboration & interaction: Maintains stable internal relationships within the immediate engineering and production team; relays information rather than driving decisions
Typical experience: 0–1 years; new graduate or intern with an engineering degree

Skills at this level

Process design and improvement: — Designs, develops and optimizes manufacturing processes and workflows to improve efficiency, reduce waste and ensure products are built to specification
Manufacturing equipment and material selection: — Assesses and selects appropriate production equipment and materials, conferring with vendors and validating choices against product requirements and process needs
Line layout and workflow analysis: — Analyzes workflow, space requirements and equipment layout to plan work cells and production lines that maximize throughput and efficiency
Assembly and test method development: — Specifies and implements assembly and test methods for a product line and drives their optimization on the production floor
Lean Manufacturing / Continuous Improvement: — Applies lean methods to reduce waste and increase efficiency across manufacturing processes; a foundational discipline for the manufacturing engineer
'Should cost' analysis: — Uses 'should cost' methods to estimate and analyze the cost of manufacturing processes, balancing cost-effectiveness against quality and delivery standards
Engineering science and technology knowledge: — Applies engineering principles, techniques, procedures and equipment to the production of goods, including knowledge of raw materials, production processes, quality control and costs
Mathematics and statistical analysis: — Uses arithmetic, algebra, geometry, calculus and statistics — including tools such as Minitab — to analyze process data and solve manufacturing problems
CAM software: — Uses computer-aided manufacturing software (e.g., CNC Mastercam, TekSoft CAMWorks) to program and define how parts are machined and produced
Design and process research programs: — Designs and conducts research programs that evaluate existing manufacturing processes and identify improvements to methods and workflow
Cross-functional coordination: — Coordinates and collaborates with design, quality, maintenance and production teams to bring processes from concept through qualified production and product launch
Production support and troubleshooting: — Provides hands-on engineering support to diagnose and resolve process, yield and equipment problems on the production line
Engineering team leadership and mentorship: — Trains, develops and mentors manufacturing engineers and coordinates project activities, providing technical direction across the engineering organization

Model-authored from 24 retrieved sources, then adversarially reviewed by an independent judge panel and held to a minimum-evidence floor before publication. Distinct from corpus-extracted content, which is labelled as such.

Pay across the ladder

Manufacturing Engineering — median with , by . Real canon data.

Pay figures are modeled estimates from our market equation — level-differentiated, with honest-wide bands. They refresh as new leveling evidence lands; treat per-role dollars as directional.

Demand — is the field growing, or just turning over?

SOC 17-0000 · national

Employment growth 2019–2024, BLS OEWSobserved

+20.1%Industrial Engineers · United States

291,710 → 350,230 jobs

25,200 openings / year, split into:

growth 3,862

replacement / exits 21,338

Growth — new jobs (15%)Exits — backfill (85%)

15% of hiring here is genuine expansion; the rest backfills people who move on.

Projected growth 2024–34 expanding: +11.0%
Growth share of hiring: 15%
Exit / retention pressure moderate: 85%
Openings / year: 25,200

Two quantities, kept apart: observed = employment growth differenced from two BLS OEWS vintages (what already happened); projected = BLS Employment Projections 2024–34, openings decomposed into growth + exits (growth derived from projected employment change). Neither is a pay figure.

Where this role sits — growth vs. pay

level P1 held

Demand axis is projected growth (not raw openings — that just measures churn). A curated, de-duplicated set of recognizable occupations held at this level; this role is highlighted.

Where it pays — by metro

OEWS metro median

San Jose-Sunnyvale-Santa Clara, CA$106k

San Francisco-Oakland-Fremont, CA$95k

Washington-Arlington-Alexandria, DC-VA-MD-WV$88k

Boulder, CO$87k

Seattle-Tacoma-Bellevue, WA$87k

Boston-Cambridge-Newton, MA-NH$83k

Lexington Park, MD$81k

Trenton-Princeton, NJ$81k

Pay only — metro-level demand isn't in public data (it needs job postings). National median $64k; the demand-cube initiative will add growth-by-metro.

What changes across the ladder

Level-distinction canon isn't available for the adjacent levels of this profile yet.

Level differentiators

What separates P1 (P1 — Entry-Level Professional) from the levels around it — this level only. Every word is real canon for this profile.

Scope: Own tasks within a defined component
Autonomy: Close supervision; work reviewed frequently
Complexity: Routine problems with known solutions
Impact: Own deliverables
Decision rights: Few independent decisions; escalates the rest
Leadership: None — building the craft

Full level-by-level matrix (side by side across the ladder) lives on the Ladder drill-down — not here.

Promotion

The next rung from P1 is P2.

Performance criteria for this profile render in the assessment kit →

People also watch

Nearest coordinate neighbors — same , same level. Each row's (confident / review / no match) comes from its — computed, not curated.

Profile	Key	Median	Δ structural
VP of Manufacturing Engineering	jf_manufacturing_engineering::E1	$174,847	confident0.06
Manufacturing Engineering Supervisor	jf_manufacturing_engineering::M1	$88,342	confident0.06
Manufacturing Engineering Technician	jf_manufacturing_engineering::S1	$38,510	confident0.06
Manufacturing Engineer	jf_manufacturing_engineering::P2	$74,658	confident0.06

Capability cluster

O*NET 17-2112

Core to this role. Click any element with an ⓘ for its O*NET definition. A job-specific capability model (SkillFrame) will sharpen this and add worked examples.

The Job Swatch

P1

jf_manufacturing_engineering::P1

Associate Manufacturing Engineer

Manufacturing Engineering

The swatch is JobFrame's core primitive: a hueset deterministically by the role's superfunction, the profileKey as its color code, the level ladder, and a content fingerprint. Two swatches that look alike are alike.

Because every role carries computable coordinates, similarity, leveling, and pricing become measurable instead of arguable— the whole point of "Pantone for jobs."

Structural

structural@1

Where it sits— position in the work taxonomy + level (weighted Gower, level > function > focus).

Track: P
Superfunction: manufacturing
Function: manufacturing_expansion
Family: manufacturing_engineering
Universal level: 1 / 8

Content

content@2

What it's about— a fingerprint over the role's tasks & capabilities.

Two roles can sit far apart structurally yet be close in content — that gap is itself a signal.

3-state matching

How any two swatches compare — a real distance in coordinate space, resolved to a calibrated verdict (never a fake "94% match").

Chemistry, Manufacturing & Controls (CMC) · P1review0.17

Lean Manufacturing · P1review0.17

Machine Shop · P1review0.17

Maintenance · P1review0.17

Pilot Plant Operations · P1review0.17

Production Test · P1review0.17

Editions — frozen & versioned

structural@1live

Released 2026-06-17

content@2live

Released 2026-07-28

pay@2live

Released 2026-07-02

semantic@1live

Released 2026-07-02

Coordinates belong to a frozen, versioned edition — a coordinate computed today still means the same thing next quarter. Re-fitting issues a new edition, so comparisons are never silently redefined.

How to read this profile

Every number here is traceable — to a named source, a stated method, and an as-of date — and each value is labeled by how we know it: observed from data, computed by a model, projected forward, or governed canon. Nothing is a black box, and nothing is invented to fill a gap.

Where every number comes from

What	Source & method	Edition	State
Median pay + range	JobFrame pay equation (function base × family multiplier × level × focus differential)	pay@2	computed
Pay across the ladder	Same equation applied at each universal level	pay@2	computed
Demand — growth & openings	BLS Employment Projections; openings decomposed into growth + exits	EP 2024–34	projected
Pay by metro	BLS OEWS metropolitan medians	OEWS 2024	observed
Level distinctions	JobFrame universal-level canon (scope · autonomy · complexity · impact · decision rights · leadership)	canon	canon
Capability cluster	O*NET Knowledge / Skills / Abilities	O*NET 17-2112	computed
Coordinates	JobFrame coordinate system — structural (weighted Gower) + content fingerprint	structural@1 · content@2 · pay@2 · semantic@1	computed
Related roles	Nearest neighbors in the structural coordinate space	structural@1	computed

The principles behind the numbers

Ranges, not false precision

Pay is P10 · median · P90, never a single misleading number.

Three honest states, never a fake %

Role matches resolve to confident / review / no-match — a calibrated verdict, not a made-up percentage.

Provenance on every value

Each number carries whether it's observed, computed, projected, or canon — so you always know how much to lean on it.

Gaps shown as gaps

When a figure isn't available at the grain you need, we say so — we don't fabricate a number to fill the cell.

Frozen, versioned editions

Pay and coordinate editions are pinned, so a comparison you make today still means the same thing next quarter.

Privacy by min-N

Any aggregate over people is suppressed below a minimum count, so no individual is identifiable.

Freshness

As of2026-07-30Editioncanon-v2@2.1.0-completeSourcecanon-v2 cell + salary-benchmark (model)