Machine Learning Engineer
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We are seeking a skilled Machine Learning Engineer to design and build intelligent systems that match the right resources to the right tasks, generate optimized schedules, and summarize project statuses using the latest in applied machine learning and large language models.
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Key Responsibilities:
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* Design, develop, and deploy ML models for real-world features, such as forecasting, smart scheduling, and recommendation systems.
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* Implement solutions leveraging Large Language Models (LLMs) from providers like OpenAI, Hugging Face, and Anthropic, incorporating advanced capabilities including additional training, retrieval-augmented generation (RAG), and reasoning.
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* Collaborate with cross-functional teams to identify opportunities to embed ML into the product experience.
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* Evaluate and optimize model performance to ensure transparency, fairness, and trust in AI-driven features.
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* Lead the development of MLOps workflows for versioning, deployment, monitoring, and retraining of production models.
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* Translate ambiguous product problems into well-defined ML problems with measurable success metrics.
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* Communicate insights and technical decisions clearly to non-technical stakeholders.
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* Mentor engineers to strengthen their skills in AI/ML development, deployment, and best practices.
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Qualifications:
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* Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Engineering, or related field.
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* 3–5+ years of experience in ML or data science roles, preferably in a SaaS or technology environment.
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* Demonstrated success shipping ML features in production environments.
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Required Skills and Qualifications:
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* Experience integrating ML into user-facing features.
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* Ability to frame business and user problems as ML problems.
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* Deep understanding of user experience considerations such as explainability, latency, and trust.
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* Proficient in working with production-grade data pipelines (SQL/NoSQL, ETL/ELT, data lakes).
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* Experience with ML model deployment using tools like Docker, FastAPI, and cloud platforms (AWS or GCP).
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* Familiarity with MLOps tools such as MLflow, Airflow, n8n, or Feature Stores.
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Benefits:
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* A supportive and talented team.
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* Hybrid work flexibility.
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* Performance-based bonus plan.
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* Life events program.
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* Employee assistance program (EAP).
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* Quarterly recognition awards.
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Others:
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We are an equal opportunity employer and warmly welcome applications from candidates of all backgrounds.