Machine Learning Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Take ownership of machine learning powered features from conception to deployment, collaborating with product, design, and engineering teams to define the scope of work and establish success metrics.

• Acquire and disseminate domain knowledge, addressing product-specific inquiries and documenting insights for team reference.

• Independently prioritize tasks, balancing feature development, quality assurance, and maintenance while clearly communicating trade-offs.

• Actively seek and provide support to colleagues through pairing, reviewing, and collaborating to advance projects.

• Understand and troubleshoot our deployment pipelines, covering build, test, and release processes for machine learning services and data pipelines.

• Utilize our monitoring and observability tools to efficiently triage alerts and incidents, working with partners to restore service and prevent future occurrences, while participating in the team’s on-call rotation and incident response.

• Act as a subject matter expert for the features and services you manage, including their data contracts, service level agreements (SLAs), and dependencies.

• Regularly engage with AI tools and advocate for their adoption across the organization.

⛳️ Requirements

• A minimum of 4 years of professional experience in applied Machine Learning or closely related domains (or a comparable combination of education and experience).

• Extensive and proven capability to navigate the entire ML lifecycle: exploratory data analysis, feature engineering, data visualization, feature and algorithm selection, model experimentation, training and validation, model serving, monitoring, and retraining.

• Experience in developing and implementing statistical and machine learning models to identify patterns, trends, and predictions in areas such as revenue forecasting, churn analysis, personalization and recommendation, anomaly detection, or natural language processing.

• Practical experience in deploying ML models using a managed service (for instance, Vertex AI or SageMaker) for high-traffic, low-latency, large-data applications that have generated significant impact for end users.

• Knowledge of foundation models and the open-source ecosystem, including model fine-tuning and prompt engineering for real-world applications.

• Strong programming skills (Python / Scala / Java / SQL, etc.) along with data engineering expertise.

• Proficient in ML frameworks such as Keras, TensorFlow, and PyTorch, as well as ETL and ML workflow frameworks like Apache Spark, Beam, Airflow, and VertexAI.

• Experience handling time series data and associated machine learning challenges, with a working understanding of semantic search and embeddings.

• Ability to recognize when assistance is needed and a willingness to learn whatever is necessary to complete tasks; a curiosity and growth mindset are essential.

• Excellent verbal and written communication skills, with the capacity to convey complex technical concepts to both technical and business stakeholders.

• Must be authorized to work lawfully in the United States, as Calendly does not participate in immigration sponsorship.

🏝️ Benefits

• Health insurance

• 401(k) matching

• Paid time off

• Flexible work hours

• Professional development opportunities

• Top Performer Bonus program

• Equity awards