Software Engineer
$50 - $60 per hourCollabera
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Days Left: 4 days, 10 hours left Apply Position Details Job Title: Python Developer Duration: 6 months 100% Remote Pay Range: $50/hr - $60/hr What you'll work on
- AI assistants have made writing code dramatically faster.
- They have not made writing correct code dramatically faster - that gap is widening, and the tooling that closes it matters more than it used to.
- That's the work this role exists to do.
- A common thread runs through everything we build: a formal specification - a schema, a contract, a grammar - is the source of truth, and the tooling we write makes other code conform to that specification automatically.
- When the specification is the source of truth, code that doesn't match it fails loudly rather than silently - whether that code was written by a human, generated by an AI assistant, or somewhere in between.
- Predicate & invariant framework for data contracts - the core of the role.
- Design and implement declarative contract classes that attach to Python methods (design-by-contract decorators - no relation to the Machine Learning data annotations below) and trigger verification of the code inside, using AST-level analysis.
- Predicates enforce data contracts: they state what a method must guarantee about the data it produces or consumes, and the verifier checks the implementation against those statements.
- Invariants constrain evolution: they state properties of the codebase that must survive change, so that modifications - human- or AI-authored - that would break them fail at verification time, not in production.
- You'll shape the vocabulary of predicates and invariants together with the architect, build the verifier and its diagnostics, and make violation messages clear enough that they teach the contract they enforce.
- Annotation data platform evolution.
- Extend a shipped canonical schema (Avro) and adapter layer that normalize Machine Learning annotation data from multiple commercial labeling platforms into a shared representation.
- Add adapters for new platforms, evolve the schema under a versioned spec and ADR process, and keep validation utilities and Python typing overlays in sync with the schema.
- Design and implement the predicate/invariant framework: contract classes, the AST-based verifier, and CI integration.
- Turn abstract contract concepts into APIs and diagnostics that working engineers adopt willingly - making the ideas graspable is part of the job, not an afterthought.
- Extend and evolve schemas, adapters, and validation layers for the annotation platform under its established change process.
- Investigate verification and validation failures and determine whether the fix belongs in the contract, the code, or the source system, documenting your reasoning.
- Document the framework thoroughly and transfer knowledge continuously - by the end of the engagement, the team must be able to own and extend it without you.
- Work closely with a senior architect on initial designs, then independently own implementation in your areas.
- We're flexible on background, but you should be able to demonstrate: Comfort with formal and abstract structures - logic, type systems, program analysis, algebraic thinking - demonstrated by working software you built from them.
- Vision and execution together; neither alone is enough.
- Deep production Python: decorators, descriptors, metaclasses, type hints, and the standard library.
- Strong analytical reasoning: comfort working from ambiguous or underspecified ideas and finding structure.
- Ability to communicate technical ideas clearly in writing (design docs, code reviews, documentation, async messaging).
- Independence in scoping and delivering work, with the judgment to escalate complex design questions.
- A computer-science degree, or any particular number of years of experience.
- Prior data engineering or Machine Learning experience (the role is adjacent to ML, not part of model training).
- Experience with our exact stack (Avro, Databricks, Spark, dbt, etc. can be learned on the job).
- Contracts and verification
- Design-by-contract tooling (icontract, deal, Eiffel, JML, Dafny) or other program-verification exposure.
- Property-based testing (Hypothesis or similar).
- Code-as-data work
- Parsing or analyzing source code (Python ast / libcst, tree-sitter, or equivalents); codemods; mypy plugins or typing internals.
- Code generation, templating, or compiler back-ends - especially if you've maintained a code generator in production.
- Rule and constraint systems.
- DSLs, OPA/Rego, rule engines, or knowledge-representation/constraint languages (OWL, RDF, SHACL, Datalog).
- Translating declarative business rules into executable validation logic.
- Schema and validation tooling
- Avro, JSON Schema, OpenAPI/Swagger, LinkML, CUE, or similar; Pydantic, Marshmallow, or attrs with validators.
- Python
- AST
- Avro
- Machine Learning
- AI
- Recruiter
- Phone
- Sushmita Singh
- View email address on click.appcast.io
Vacancy posted 2 days ago
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