Calendly01/20/2026
Инженер по машинному обучению
Salary not specified
MARKET
16,167 ₽median for this role
Data Scientist · 96 jobs with disclosed pay
5,800half of the offers: 13,208–20,77743,793
The employer didn't disclose pay — compare with the market yourself.
Remote - US
Responsibilities
- 01Own ML powered features from design through deployment, partnering with product, design, and engineering to scope work and define success metrics
- 02Understand and share domain knowledge, answering domain specific questions for your product area and documenting what you learn for the team
- 03Prioritize your work independently, balancing feature development, quality, and maintenance, and communicating tradeoffs clearly
- 04Proactively seek and offer support to teammates pairing, reviewing, and collaborating to move projects forward
- 05Understand and troubleshoot our deployment pipelines, including build, test, and release steps for ML services and data pipelines
- 06Use our monitoring and observability tools to effectively triage alerts and incidents, collaborating with partners to restore service and prevent recurrence, and participate in the team’s on-call rotation and incident response
- 07Serve as a subject matter expert for the features and services you own, including their data contracts, SLAs, and dependencies
- 08Be a frequent user of AI Tools and champion of adoption to the rest of the company
Requirements
- 014+ years of industry experience in applied Machine Learning or closely related fields (or equivalent combination of education and experience) with a demonstrated track record of shipping and operating ML models in production
- 02Deep and demonstrated ability to traverse the full spectrum of ML life cycle: exploratory data analysis, feature engineering, data visualization, feature and algorithm selection, model experimentation, model training and validation, model serving, monitoring and retraining
- 03Experience developing and implementing statistical and ML models to uncover patterns, trends, and predictions in areas such as revenue forecasting, churn analysis, personalization and recommendation, anomaly detection, or natural language processing
- 04Hands-on experience implementing ML models using a managed service (for example, Vertex AI or SageMaker) for high-traffic, low-latency, large-data applications that produced tangible impact for end users
- 05Understanding of foundation models and the open-source ecosystem, including model fine-tuning and prompt engineering for real product use cases
- 06Strong programming (Python / Scala / Java / SQL etc) and data engineering skills
- 07Proficiency in ML frameworks such as: Keras, Tensorflow and PyTorch and ETL and ML workflow frameworks like Apache Spark, Beam, Airflow and VertexAI
- 08Experience working with time series data and related machine learning problems
- 09Working knowledge of semantic search and embeddings
- 10Recognize when to seek assistance and willing to learn whatever is needed to get the job done; curiosity and growth mindset are essential
- 11You have strong verbal and written communication skills
- 12Ability to communicate complex technical concepts to both technical and business stakeholders
- 13You are comfortable working remotely and with enabling tools like Slack, Confluence, etc
- 14Authorized to work lawfully in the United States of America as Calendly does not engage in immigration sponsorship at this time