Engineer, Machine Learning

Link Logistics•New York, NY

13d•$175,000 - $195,000

About The Position

Link Logistics Real Estate (“Link”) is a leading operator of warehouses and business parks, specializing in last-mile logistics real estate. Established by Blackstone in 2019, the company connects consumption, technology, and the supply chain across its portfolio, which spans half a billion square feet. We leverage our scale, proprietary data and insights, and foundational focus on sustainability to drive success for our customers’ businesses and deliver value for our stakeholders. We put our people, customers, and communities first and find ways to make a conscious, positive impact where we live and work. Every day, we work to reinvent and lead our industry forward by thinking bigger and challenging the status quo. As a Machine Learning Engineer, your primary responsibilities will be to productionize supervised and unsupervised models, as well as advanced analytics. You are conversant in several standard machine learning algorithms. You are comfortable optimizing pipelines, reorganizing or rewriting code for ML and AI, evaluating cluster handling, and algorithmic performance and reliability. You collaborate with our Customer Experience and Innovation teams, Sustainability team and Research team to make their work real for the business.

Requirements

Experience ~3-5 years of success in ML/AI and production pipelines and in employing MLOps tools and practices.
Monitoring Skills Experience with metric building, monitoring and maintaining ML pipelines in production environments.
Technical Proficiency Deep expertise in Python, Spark, Spark Scala, or R. Experience with scalable distributed systems.
Problem Solving . Ability to identify technical hurdles, and proactively build or suggest solutions.
Collaboration and Communication . Acknowledged for driving decisions collaboratively, resolving conflicts and ensuring follow through with exceptional verbal and written communication skills.
Technical experience with production pipelines: Deep expertise in some combination of these languages Python, Pyspark, Spark Scala, R Hands-on experience with ML frameworks (e.g. TensorFlow, Scikit-learn, etc) Strong SQL skills for querying databases, performing data analysis, and generating insights. Experience with scalable distributed systems (e.g. Databricks, Spark) Experience with MLOps tools and platforms to automate ML workflows. Strong SQL skills for querying databases, performing data analysis, and generating insights. Experience using cloud platforms such as MS Azure

Nice To Haves

Masters Preferred Bachelor's degree in Computer Science, Data Science, Statistics, or related field, or equivalent work experience.

Responsibilities

Implement and manage MLOps practices to automate and streamline the machine learning lifecycle, ensuring fast and reliable ML model deployment and monitoring.
Monitor, update, and maintain the performance and reliability of deployed models.
Implement testing and validation processes to ensure the reliability and effectiveness of models.
Work hand-in-hand with Data Scientists and other teams to productionize their ML and analytical solutions.
Collaborate with the Customer Experience, Research and Sustainability teams, as well as data engineers and other analysts.
Proactively bring your experience to bear in conversation with technical and non-technical stakeholders.