Machine Learning Engineer (Xico)

Position Overview

We are seeking a Senior Consultant with strong software and machine learning engineering experience to design, build, and operate scalable data and ML systems. This role focuses on developing production-grade platforms, APIs, and pipelines that enable data-driven decision-making and business outcomes. You will work closely with software engineers, data scientists, product managers, and platform teams to deliver reliable, observable, and scalable ML solutions. The role requires both hands‑on technical execution and the ability to think strategically about system design, operational excellence, and long‑term platform evolution.

Key Responsibilities

System & Software Design

• Design and develop moderately complex, testable, and observable software systems. Contribute to architectural discussions, particularly for big data and machine learning applications.
• Apply systems thinking to identify improvements that scale beyond individual projects.

API & Platform Development

• Build and maintain reusable APIs and services consumed across multiple business units. Ensure solutions are scalable, secure, and aligned with software engineering best practices.

Machine Learning Engineering

• Build and maintain end‑to‑end ML pipelines in production, including feature engineering, model training, validation, and inference.
• Optimize ML systems for performance, reliability, and scalability in distributed environments.

Data & Distributed Processing

• Work with large datasets using Spark and distributed computing patterns. Train and deploy models using GPUs or distributed compute where appropriate.

Operational Excellence

• Implement monitoring, logging, and alerting to meet SLA and reliability expectations.
• Participate in root cause analyses (RCAs) and technical deep dives.

Collaboration & Mentorship

• Collaborate with engineering, data, and product stakeholders to align priorities.
• Lead code reviews, mentor peers, and promote engineering best practices.
• Document and communicate technical concepts clearly to both technical and non‑technical audiences.

Innovation & Continuous Improvement

• Identify inefficiencies in systems and codebases and propose platform or tooling improvements.
• Stay current with emerging technologies and share knowledge within the engineering community.

Required Experience & Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field, or equivalent professional experience.
• 3+ years of experience in software engineering and/or machine learning engineering.
• Strong programming skills in Python, plus experience developing software in at least three programming languages, with deep expertise in at least one.
• Proven experience building and operating production ML pipelines end to end.
• Hands‑on experience with PyTorch, TensorFlow, and scikit‑learn.
• Strong knowledge of Spark (PySpark, map‑reduce patterns) and large‑scale data processing.
• Experience with cloud services on AWS, including storage (e.g., S3) and IAM concepts.
• Experience with workflow orchestration tools such as Airflow and/or Flyte.
• Solid understanding of software engineering principles, data structures, and design patterns.
• Experience designing testable systems and debugging issues within SLA constraints.
• Familiarity with monitoring and observability tools such as Datadog.
• Prior consulting experience working across multiple teams or business units.
• Strong technical writing and presentation skills.

Preferred Qualifications

• Experience building or integrating LLM‑based solutions in production environments.
• Experience with streaming applications in cloud or hybrid architectures.
• Prior consulting experience working across multiple teams or business units.
• Strong technical writing and presentation skills.