Allocate Logo

Allocate

Machine Learning Engineer

Reposted One Month Ago
Remote
Hiring Remotely in USA
165K-185K Annually
Mid level
Remote
Hiring Remotely in USA
165K-185K Annually
Mid level
Build, train, fine-tune, evaluate, and deploy machine learning and LLM models for production. Create monitoring, evaluation, and feedback tooling, evaluate new techniques, and collaborate cross-functionally to ship ML-powered features.
The summary above was generated by AI
About Allocate

Allocate is transforming private market investing by enabling RIAs and family offices to seamlessly discover, model, and manage their private market exposure. Our platform combines curated fund and co-investment opportunities with institutional-grade infrastructure. Through a single, data-rich digital experience, clients access top-tier opportunities across venture capital, private equity, private credit, and other private asset classes—backed by powerful tracking, analytics, and administration tools.

About the Role

Allocate is looking to add an AI / Extraction Engineer to the team! There's a lot for us to build, and we need a strong engineer with a broad skillset who can jump right in to help us lay the technical foundation for the company's future.

Essential Responsibilities and Duties
  • Build, train, and improve machine-learning models for production use.

  • Develop evaluation and feedback loops that measurably improve model performance over time.

  • Stand up the tooling to measure, monitor, and track model quality.

  • Evaluate new models and techniques, and bring the best into production.

  • Collaborate cross-functionally to ship ML-powered capabilities.

Must Have Experience
  • 4+ years of applied ML / LLM engineering in production, with strong Python.

  • Experience taking models from prototype to reliable production systems.

  • Hands-on model fine-tuning and rigorous evaluation discipline.

  • Proficiency with Git and version control systems.

  • Hands-on experience with AI-assisted development tools such as Claude Code, OpenAI's Codex, or Cursor, and a demonstrated ability to incorporate new tools as they emerge.

Nice to Haves
  • Applied NLP, computer vision, or multimodal models.

  • MLOps and model-monitoring tooling.

  • Background in fintech or financial data.

Education
  • Bachelor's degree in Computer Science, a similar technical field, or equivalent practical experience.

Essential Values & Culture
  • Providing our clients with a world-class experience is our number one priority. We obsessively search for ways to improve the experience for our clients and partners—extraordinary response times, proactivity, and a top-tier experience in everything from product strategy to offline communications.

  • Challenge convention: Instead of detailing all the reasons an idea may not work, we question things to determine how a viable idea may be put into motion.

  • Commitment to continuous improvement: We find ways to personally scale each day by pushing ourselves up the learning curve.

  • Meritocracy, not politics: We place the utmost value on results and reward through merit, not political agendas.

  • Civil Discourse is embraced: Open, intellectually curious conversations are required to consistently arrive at the best decisions. Respect is paramount, but the mission is to get the right answer collectively, not to be right.

  • Embrace technological change: We adopt tools and techniques that make us faster, smarter, and better—especially around AI and automation—and drop outdated methods without hesitation.

Additional Details
  • Location: Fully Remote (all I-9 eligible candidates will be considered).

  • Employment: Full-time. Seniority: Senior professional.

  • Salary: The expected base salary range for this role is $165,000 to $185,000. Actual compensation will be determined based on the candidate's primary work location and other job-related factors including skills, experience, qualifications, interview performance, internal equity, and market data. Candidates located in higher cost-of-living markets, including the San Francisco Bay Area, may be considered within the higher end of the range. This range reflects base salary only and does not include bonus, equity, or benefits; total compensation may also include a discretionary performance-based bonus.

  • Benefits: Medical, dental, and vision; 401(k); and responsible vacation time (PTO).

  • Travel required for team and department offsites. An in-person interview may be required during the process. A broadband internet connection is required. Compliance with Allocate's Code of Ethics is a given for this role.

Similar Jobs

Yesterday
In-Office or Remote
120K-215K Annually
Senior level
120K-215K Annually
Senior level
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Design, deploy, and improve enterprise AI solutions including LLM workflows, RAG pipelines, agents, classifiers, and copilots. Develop prompt strategies, tool-calling patterns, guardrails, evaluation frameworks, and responsible AI controls. Partner with data, security, privacy, compliance, architecture, and QA teams to ensure solutions are safe and governed. Monitor production quality, accuracy, hallucination risk, latency, cost, observability, and model drift while documenting limitations and operational requirements.
Top Skills: Agent FrameworksData PipelinesEmbeddingsEvaluation ToolingLlmsModel ApisModel MonitoringModel ObservabilityOrchestration FrameworksPrompt EngineeringPythonRagVector Search
2 Days Ago
In-Office or Remote
120K-215K Annually
Senior level
120K-215K Annually
Senior level
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Design, develop, deploy, and operate production AI/ML systems, including conversational chatbot and virtual assistant platforms. Build and optimize machine learning models, MLOps frameworks, CI/CD pipelines, and containerized deployments. Collaborate with architecture teams, business stakeholders, and technology vendors to create secure, scalable solutions. Maintain architecture diagrams, promote observability and automation, evaluate emerging AI trends, and support model governance, privacy, and ethical AI practices.
Top Skills: Artificial IntelligenceCi/CdDeep LearningDockerFine-TuningJavaKubernetesLarge Language ModelsMachine LearningMicrosoftMlopsMongoDBNatural Language ProcessingPalantirPrompt EngineeringPythonRetrieval-Augmented GenerationScalaSQL
2 Days Ago
In-Office or Remote
148K-233K Annually
Entry level
148K-233K Annually
Entry level
Cloud • Information Technology • Productivity • Security • Software • App development • Automation
Build and ship intelligent search capabilities for Atlassian’s Rovo Chat and AI workflows. Responsibilities include developing ML-powered search features spanning query understanding, retrieval, ranking, and answer generation; maintaining production ML pipelines; applying reranking, embeddings, and reinforcement learning; conducting offline evaluations and online A/B tests; collaborating cross-functionally; and improving evaluation infrastructure and data tooling.
Top Skills: A/B TestingEmbedding ModelsInformation RetrievalLarge Language ModelsMachine LearningNlpReinforcement LearningRovo

What you need to know about the Charlotte Tech Scene

Ranked among the hottest tech cities in 2024 by CompTIA, Charlotte is quickly cementing its place as a major U.S. tech hub. Home to more than 90,000 tech workers, the city’s ecosystem is primed for continued growth, fueled by billions in annual funding from heavyweights like Microsoft and RevTech Labs, which has created thousands of fintech jobs and made the city a go-to for tech pros looking for their next big opportunity.

Key Facts About Charlotte Tech

  • Number of Tech Workers: 90,859; 6.5% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Lowe’s, Bank of America, TIAA, Microsoft, Honeywell
  • Key Industries: Fintech, artificial intelligence, cybersecurity, cloud computing, e-commerce
  • Funding Landscape: $3.1 billion in venture capital funding in 2024 (CED)
  • Notable Investors: Microsoft, Google, Falfurrias Management Partners, RevTech Labs Foundation
  • Research Centers and Universities: University of North Carolina at Charlotte, Northeastern University, North Carolina Research Campus

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account