Ohalo Logo

Ohalo

Senior Machine Learning Engineer

Sorry, this job was removed at 01:11 p.m. (PST) on Wednesday, Apr 15, 2026
Be an Early Applicant
In-Office
South San Francisco, CA, USA
In-Office
South San Francisco, CA, USA

Similar Jobs

7 Hours Ago
Remote or Hybrid
United States
125K-211K Annually
Senior level
125K-211K Annually
Senior level
Artificial Intelligence • Cloud • Sales • Security • Software • Cybersecurity • Data Privacy
Designs, develops, deploys, and operates production machine learning and AI systems for identity security. The role spans classical ML, generative AI, foundation models, RAG, agentic workflows, semantic search, behavioral modeling, and graph ML. Responsibilities include experimentation, model evaluation, monitoring, MLOps, AI governance, architecture, cross-functional delivery, and continuous improvement of scalable customer-facing capabilities.
Top Skills: Agent FrameworksAmazon BedrockAmazon SagemakerApache AirflowApache IcebergApache KafkaAWSCi/CdCloudbeesDbtFeastFoundation ModelsGoJenkinsLlmsMlopsPythonPyTorchRetrieval-Augmented Generation (Rag)Scikit-LearnShell/BashSnowflakeSQLTensorFlow
21 Hours Ago
Easy Apply
Hybrid
San Francisco, CA, USA
Easy Apply
228K-317K Annually
Senior level
228K-317K Annually
Senior level
Fintech • Payments • Financial Services
Design, productionize, and operate machine learning models and rule-based decision systems for credit underwriting. Build scalable pipelines for feature engineering, training, validation, deployment, monitoring, and continuous improvement. Optimize ML performance, integrate models into products, collaborate with software, risk, data, and product teams, and promote strong engineering and MLOps practices across production systems.
Top Skills: AirflowArgo WorkflowsDockerGrafanaJavaKubernetesLightgbmMlflowPandasPrometheusPysparkPythonPyTorchTensorFlowTrino SqlXgboost
Yesterday
In-Office or Remote
San Francisco, CA, USA
171K-269K Annually
Senior level
171K-269K Annually
Senior level
Cloud • Information Technology • Productivity • Security • Software • App development • Automation
Develop and productionize machine learning systems for search, retrieval, ranking, recommendations, conversational experiences, and AI agents. Own projects across the ML lifecycle, build evaluation datasets and benchmarks, conduct offline and online evaluations, analyze model quality, and improve system performance. Design scalable architectures addressing reliability, latency, privacy, and cost. Collaborate across product and engineering teams, communicate technical decisions, mentor engineers, and contribute to ML best practices.
Top Skills: Agentic SystemsSparkAWSDatabricksDeep LearningEmbeddingsInformation RetrievalJavaKotlinLarge Language ModelsNlpPythonRagRankingRecommendationsSQLTypescript

Position Title: Senior Machine Engineer / Lead
Location: San Francisco, CA
Time Type: Full Time


The Opportunity

Ohalo is looking for a hands-on Senior Machine Learning Engineer / Lead to convert cutting-edge quantitative-genetics and computer vision research into production systems that accelerate crop improvement. You will steer a squad of ML/Data/Software Engineers, partnering with quantitative geneticists and statisticians to deliver Bayesian genomic-prediction pipelines, breeding-system simulations, and AI-powered hybrid-optimization services. Your work will directly shape how breeders make thousands of crossing decisions and drive the next leap in agricultural productivity.

Responsibilities
  • Design, build, and maintain scalable ML pipelines on GCP (or the best-fit cloud) using Python, BigQuery/Spark, Kubernetes, and CI/CD best practices.
  • Mentor & grow a small team—provide technical guidance, establish code-review norms, and cultivate a culture of rapid, well-engineered experimentation.
  • Own model-ops lifecycle: automated testing, containerized deployment, continuous monitoring, and A/B evaluation against breeding KPIs.
  • Collaborate cross-functionally with plant scientists, data engineers, and the automation group to ingest high-throughput phenotyping data and close feedback loops.
  • Establish MLOps Excellence: Build robust infrastructure for model versioning, data lineage, and automated retraining; implement "champion-challenger" deployment patterns to safely promote research models to production while ensuring full auditability of breeding decisions.
Required Qualifications:
  • Education – M.S. in Computer Science or related field (or equivalent industry record).
  • Experience – 5+ years building production ML/AI systems, technical lead experience preferred
  • Engineering excellence – Expert Python plus one ML framework (JAX/NumPyro, TensorFlow, or PyTorch); strong grasp of microservices, Docker/Kubernetes, and cloud data platforms (BigQuery, Vertex AI, etc.).
  • Data-engineering acumen – Comfortable designing batch, streaming, and event-driven pipelines; Pub/Sub, Kafka, or equivalent.
  • Leadership & communication – Able to set direction, give candid feedback, and bridge domain-scientist ↔ engineer conversations with clarity.

Nice to have:

  • Advanced Image Techniques – Proficiency in leveraging Foundation Models (e.g., SAM, CLIP) and Self-Supervised Learning to automate high-throughput feature extraction, converting unstructured imagery into high-dimensional embeddings for advanced statistical analysis.

About Ohalo: 

Ohalo™ aims to accelerate evolution to unlock nature's potential. Founded in 2019, Ohalo develops novel breeding systems and improved plant varieties that help farmers grow more food with fewer natural resources, increasing the yield, resiliency, and genetic diversity of crops to sustainably feed our population. Ohalo's breakthrough technology, Boosted Breeding™, will usher in a new era of improved productivity to radically transform global agriculture. For more information, visit www.ohalo.com.

The anticipated pay range for this role is $170,000 - $220,000 per year for our San Francisco, CA location, though salary will be based on a variety of factors including, but not limited to, experience, skills, education, and location.

Notes: If you previously applied for a job at Ohalo Genetics, we encourage you to restate your interest in the position by submitting your application.

Ohalo is an Equal Opportunity / Affirmative Action employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state or local laws. Ohalo is also committed to working with and providing reasonable accommodations to individuals with disabilities. Please let your recruiter know if you need an accommodation at any point during the interview process.

No visa sponsorship is available for this position at this time. 

This organization participates in E-Verify. Posters linked here. 

No recruiters, please.

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account