Senior Software Engineer, MLOps
Forward Financing · Boston, MA
$175,000–$220,000
Jul 19, 2026
Boston, MA
Jul 21, 2026
What this job asks for AI summary
A senior backend engineering role focused on building and maintaining a real-time ML feature store — the infrastructure that computes, stores, and serves machine learning features to production models with low latency. The work spans data pipeline development (batch and streaming), Postgres schema design, and cross-team collaboration with Data Science and Analytics Engineering. Suited to engineers with strong Python and MLOps backgrounds who have operated real-time inference systems at production scale.
Senior level · 5+ years · Remote · Full-time
Pay in the description: $175,000–$220,000
“or” means any one of them counts — you don't need all of them.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Roughly 16,200 people nationally plausibly meet what this posting asks for (software developers). range 9,700–24,400
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
Rare in this occupation — lead with these, and say what you built with them.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $138,970 (middle half $107,524–$175,762). This posting is about at that midpoint.
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (9)
The role sits at the intersection of backend software engineering and MLOps/data infrastructure (online feature store, ML-serving pipelines). 15-1252 Software Developers is the primary classification because the core work is building and shipping production software systems; 15-1243 Database Architects is a plausible runner-up given the emphasis on Postgres schema design and data modeling.
The degree requirement states 'Typically has a Bachelor's degree … or additional relevant experience,' which treats the degree as substitutable — treated as not a hard gate.
MLOps experience is stated as '2-3 years' in the requirements section; the minimum (2) is captured as the years demanded on the MLOps skill.
The 5+ years of overall software experience is captured as the overall years minimum of 5 (the role-level requirement); the 2-3 years of MLOps is a skill-level sub-requirement.
Feature store tools (Feast, Tecton, SageMaker Feature Store) and MLOps tooling (MLflow, Airflow, dbt) appear under 'Bonus Qualifications' and are marked preferred accordingly.
An annual bonus of up to 10% is mentioned in addition to the $175,000–$220,000 base salary range; only the base salary range is captured in the compensation fields.
'Real-time inference systems' is listed as a required skill but names no specific product — it reflects the JD's explicit requirement for experience building and operating such systems.
Ignored 1 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): real-time inference systems.
Caller marked this a fully-remote role — scored against the national candidate pool.
Read the full posting
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