Head of ML & Data Engineering

Vacancy No VN364

Status Active

Location Remote US

Location Country United States

Location Region

Location City

Description Who are we?

Auction Technology Group (ATG) is transforming the multi-billion-dollar global auction industry. Our platforms connect thousands of auction houses with buyers in over 170 countries, powering more than $15 billion in annual sales. Through innovative online auction technologies, we help auctioneers expand their reach, boost efficiency, and maximize value—while giving bidders unrivaled access to rare and specialized items. As a publicly traded company, ATG has scaled from $18 million to $170 million in revenue, with sustained growth beyond the pandemic. We're modernizing one of the last industries to fully go digital—building a global, category-defining business in the process.

What are we hiring for?

We are making a significant investment in building a world-class ML team. The Engineering Manager will lead a cross-functional team of MLOps Engineers, Data Engineers, and ML Engineers responsible for building and scaling the infrastructure that powers our AI/ML capabilities, data pipelines, and real-time analytics across all of our marketplaces. This role requires both deep technical expertise and strong people leadership skills to build and scale a high-performing team.

Key Responsibilities What will you do?

Team Leadership \& Development

Build, mentor, and scale a team of MLOps Engineers, Data Engineers, and ML Engineers

Create career development plans, conduct performance reviews, and provide regular coaching and feedback

Foster a culture of technical excellence, collaboration, experimentation, and continuous improvement

Remove blockers and create an environment where engineers can do their best work

Technical Strategy \& Architecture

Define the technical vision and roadmap for ML infrastructure, data pipelines, and enablement capabilities

Drive architectural decisions for embedding systems, recommendation engines, search integration, and feature stores

Establish standards and best practices for MLOps including model versioning, deployment and monitoring

Balance technical debt with feature delivery while maintaining system reliability and scalability

Stay current with ML infrastructure trends and evaluate new technologies for potential adoption

Delivery \& Execution

Own the planning, prioritization, and delivery of ML infrastructure and data pipeline initiatives

Collaborate with Product Managers to translate business requirements into technical solutions

Work closely with cross-functional teams (Software Engineering, Analytics, Data Science) to ensure seamless integration

Establish metrics and KPIs to measure team performance, system health, and business impact

Drive incident response and post-mortems for ML/data systems, implementing preventive measures

Manage stakeholder expectations and communicate progress, risks, and trade-offs effectively

Operational Excellence

Ensure high availability, reliability, and performance of ML systems handling millions of daily requests

Establish monitoring, alerting, and observability practices for ML models and data pipelines

Implement CI/CD practices for ML workflows including testing, versioning, and deployment strategies

Drive cost optimization efforts across cloud infrastructure and data storage

Key Requirements What do we need from you?

Leadership \& Management Experience:

5\+ years managing engineering teams, preferably in ML/MLOps or data engineering domains

Proven track record of building and scaling high-performing teams

Experience hiring, mentoring, and developing engineers at various career stages

Strong emotional intelligence with ability to give and receive constructive feedback

Technical Expertise:

7\+ years of hands-on software engineering experience with at least 3\+ years in ML infrastructure or data engineering

Deep understanding of ML lifecycle: data preparation, feature engineering, model training, deployment, monitoring

Strong experience with MLOps tools and platforms (MLflow, Kubeflow, feature stores, model registries)

Expertise in building scalable data pipelines using tools like Airflow, Dagster, or similar orchestration frameworks

Hands-on experience with embedding systems, vector databases, and search technologies (Elasticsearch, OpenSearch)

Proficiency in Python and SQL with experience building production-grade systems

Strong knowledge of cloud platforms (AWS preferred) including services like S3, EMR, SageMaker

Past work designing data models and optimizing query performance within Snowflake

Experience with containerization (Docker), orchestration (Kubernetes), and infrastructure-as-code (Terraform, CloudFormation)

Domain Knowledge:

Understanding of recommendation systems, ranking algorithms, and personalization techniques

Experience with A/B testing frameworks and experimentation platforms for ML models

Familiarity with data streaming technologies (Kafka) and real-time processing

Knowledge of data governance, privacy regulations, and security best practices

Experience working in eCommerce, marketplaces, or consumer-facing products is a plus

Soft Skills \& Attributes:

Excellent communication skills with ability to explain complex technical concepts to diverse audiences

Strategic thinking balanced with tactical execution and attention to detail

Collaborative mindset with experience working across Product, Engineering, Data Science, and Analytics teams

Data-driven decision-making approach with strong analytical and problem-solving abilities

Comfortable operating in ambiguous environments and adapting to changing priorities

Passion for enabling others and driving impact through people and technology

Strong organizational skills with ability to manage multiple competing priorities

Nice-to-Have:

Experience in auction, marketplace, or eCommerce platforms

Experience with computer vision or NLP systems

Familiarity with dbt (data build tool) for analytics engineering workflows

Employment Type Permanent

Duration

Business Name Proxibid

Function Name Technology