2727 Csx jobs in Washington

Commissions

Discretionary bonuses

Mileage reimbursement

Cell phone allowance

Management referral

24-29 Hourly Wage

Medical insurance, vision insurance, dental insurance, life and AD&D; insurance, and long-term disability insurance.

Company provided dollars to use towards medical, dental and vision.

Retirement Plans - eligible after 1000 hours of service. Vested immediately. Company matches up to a set amount each year.

Vacation - lump sum to begin the following month of hire to equal 10 hours per month. (3 weeks)

Paid Holidays - 9 paid holidays per year.

Sick Pay - 0.038462 hours of sick per hour worked (on average 10 days per year). Up to 80 hours carryover each year.

Associate or bachelor's degree (minimum 2 years) in a related field, or equivalent experience in property management, real estate, or a related industry

Proficient in Microsoft Office Suite (Word, Excel, Outlook)

Valid driver's license with a good driving record

Reliable transportation

Property Associates are required to complete the Kiemle Hagood University (KHU) training program and obtain their Real Estate License, when applicable, within 90 days of assuming the role.

Complete the Kiemle Hagood University (KHU) training program and obtain Real Estate License within 90 days of starting position

Basic familiarity with commercial real estate or property operations preferred

Starting base salary between $60000 - $63000 / year (includes fixed and sales variable compensation)

Eligibility for sales incentives

Auto allowance

The total first year earnings may range between $75000 - $100000.

Comprehensive medical and prescription drug coverage

Dental and vision plans

Tax-saving Flexible Spending Accounts

Disability coverage

Life insurance plans

A 401(k) plan

Tuition assistance

A wellness program

Parental leave

Vacation accrual

Paid sick leave

Full-time employee

Wine knowledge required.

Will drive own vehicle daily in the Bellevue and surrounding area(s) of WA.

21 years or older

Must possess a reliable vehicle

A valid driver's license

The ability to obtain and maintain auto liability insurance on their vehicle in compliance with SGWS company requirements.

High School Diploma or GED required

Able to travel as needed

Must be at least 21 years of age

Physical demands with activity or condition may include walking, bending, reaching, standing, squatting, and stooping

Physical demands with activity or condition for a considerable amount of time include driving throughout the day with segments up to 2 hours

May require lifting/lowering, pushing, carrying, or pulling up to 48lbs

Any person who is given a conditional offer of employment will be required to pass a drug test.

Desired candidate will have both Sales and On-Premise experience.

Sign-on payments and restricted stock units (RSUs)

168,100.00 - 227,400.00 USD annually

Health insurance (medical, dental, vision, prescription, Basic Life & AD&D; insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)

401(k) matching

Paid time off

Parental leave

Experience in Dataplane development, System Software/Embedded software, Cloud Computing, and Networking

Bachelor's degree in computer science or equivalent

7+ years of non-internship professional software development experience

7+ years of programming with at least one software programming language experience

5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience

7+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience

Experience as a mentor, tech lead or leading an engineering team

Experience in embedded development in C/C++

Knowledge of system performance, memory management, and parallel computing principles

Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution

Knowledge of machine learning model architecture and inference

Experience developing low-level systems software, networking dataplane, or performance-critical services