Software Engineer, Machine Learning

Jobtailor; California (MO); On-site; USD 120,000 - 190,000; Full time

Job summary

Jobtailor is seeking a skilled ML Engineer to enhance the Slackbot experience by building ranking, retrieval, and generative AI models. You will collaborate with product and design teams to craft impactful features and lead large, cross‑functional initiatives that shape product direction.

You will mentor engineers, improve data pipelines, and drive robust ML deployments while maintaining high engineering standards and clear cross‑team communication.

Qualifications

• Experience with functional or imperative programming languages including PHP, Python, Ruby, Go, C, Scala, or Java.
• Experience with common ML frameworks such as PyTorch, TensorFlow, Keras, XGBoost, or Scikit‑learn.
• Experience fine‑tuning LLMs or BERT models.
• Experience building batch data processing pipelines using Apache Spark, Hadoop, EMR, MapReduce, Airflow, Dagster, or Luigi.
• Analytical and data‑driven mindset with ability to measure success for complex ML/AI products.
• Experience putting machine learning models or other data‑derived artifacts into production at scale.
• Experience leading technical architecture discussions and driving technical decisions.
• Ability to write understandable, testable, maintainable code.
• Strong communication skills and ability to explain complex technical concepts to designers, support teams, and specialists.

Responsibilities

• Leverage machine learning and artificial intelligence expertise to improve the Slackbot experience.
• Develop ML models for ranking, retrieval, and generative AI use cases.
• Brainstorm with Product Managers, Designers, and Frontend Engineers to conceptualize and build features.
• Lead or heavily contribute to large multifunctional projects with significant business impact.
• Own features or systems and define their long‑term health.
• Improve the health of surrounding systems.
• Support sustainable data collection pipelines and ML feature management.
• Assist support and operations teams with triaging and resolving production issues.
• Mentor engineers and conduct deep code reviews.
• Improve engineering standards, tooling, and processes.
• Build data pipelines, train recommendation models, fine‑tune LLMs, implement application features, and analyze experiment data as needed.

Skills

Functional Programming

ML Frameworks

LLM Fine-tuning

Batch Processing

Data Pipelines

Production ML

Technical Architecture

Code Review

Strong Communication

NLP Expertise

Tools

Apache Spark

Hadoop

Airflow

Keras

Scikit-learn

XGBoost

BERT

Slackbot

MapReduce

Dagster

Job description

• Leverage machine learning and artificial intelligence expertise to improve the Slackbot experience
• Develop ML models for ranking, retrieval, and generative AI use cases
• Brainstorm with Product Managers, Designers, and Frontend Engineers to conceptualize and build features
• Lead or heavily contribute to large multifunctional projects with significant business impact
• Own features or systems and define their long‑term health
• Improve the health of surrounding systems
• Support sustainable data collection pipelines and ML feature management
• Assist support and operations teams with triaging and resolving production issues
• Mentor engineers and conduct deep code reviews
• Improve engineering standards, tooling, and processes
• Build data pipelines, train recommendation models, fine‑tune LLMs, implement application features, and analyze experiment data as needed

Requirements

• Experience with functional or imperative programming languages including PHP, Python, Ruby, Go, C, Scala, or Java
• Experience with common ML frameworks such as PyTorch, TensorFlow, Keras, XGBoost, or Scikit‑learn
• Experience fine‑tuning LLMs or BERT models
• Experience building batch data processing pipelines using Apache Spark, Hadoop, EMR, MapReduce, Airflow, Dagster, or Luigi
• Analytical and data‑driven mindset with ability to measure success for complex ML/AI products
• Experience putting machine learning models or other data‑derived artifacts into production at scale
• Experience leading technical architecture discussions and driving technical decisions
• Ability to write understandable, testable, maintainable code
• Strong communication skills and ability to explain complex technical concepts to designers, support teams, and specialists
• Nice to have: expertise in conversational agentic systems
• Nice to have: expertise in retrieval systems and search algorithms
• Nice to have: familiarity with vector databases and embeddings
• Nice to have: knowledge of structured, unstructured, and knowledge graph data in RAG solutions
• Nice to have: broad experience across NLP, ML, and Generative AI capabilities

Core Competencies

Demonstrates expertise in machine learning and artificial intelligence to enhance user experiences, with a strong focus on developing and deploying ML models and data pipelines. Capable of leading multifunctional projects and mentoring engineers while ensuring high engineering standards and effective communication across teams.

Highest-signal resume keywords

• Machine Learning Model Development
• Data Pipeline Construction
• ML Frameworks (PyTorch, TensorFlow)
• Functional Programming (Python, Java, Go)
• Technical Architecture Leadership

ATS Optimization Keywords

Hard Skills

• Machine Learning
• Artificial Intelligence
• Data Processing Pipelines
• Model Fine‑Tuning
• Code Review
• Analytical Skills
• Testable Code Writing
• Batch Processing
• NLP Expertise
• Generative AI

Soft Skills

• Strong Communication Skills
• Mentoring

Industry Keywords

• Conversational Agentic Systems
• Retrieval Systems
• Search Algorithms
• Vector Databases
• Knowledge Graph Data

Tools & Technologies

• Apache Spark
• Hadoop
• Airflow
• Keras
• Scikit‑learn
• XGBoost
• BERT
• Slackbot
• MapReduce
• Dagster