Position: ML Ops Engineer  (HealthCare project, Sign-on bonus 1k)
Company: Intersog
Experience required: 5y
English level: upper

**Requirements:**
- At least 4 years’ professional experience in the data and analytics domain working in any capacity from data engineering and business intelligence to data science and machine learning;
- Upper-Intermediate written and spoken English.
Data Science:
 - At least 2 years’ experience deploying advanced analytics models in a serverless/containerized environment;
- At least 2 years’ experience with data visualization tools like Cognos, Arcadia, Tableau;
- At least 2 years’ experience with classic ML approaches, NLP, &amp; Deep Learning proficiency;
- At least 2 years’ experience developing enterprise solutions inclusive of Application Monitoring, Build Tools, Version Control, Unit Test, TDD, Change Management to support DevOps.
Data Engineering:
- At least 2 years’ experience with Spark programming (PySpark or Scala);
- At least 2 years’ experience with designing and developing Data Pipelines for Data Ingestion or Transformation using Java or Scala or Python;
- At least 2 years’ experience with SQL and Shell Scripting experience;
- At least 2 years’ experience with Streaming using Spark or Flink or Kafka
Preferred;
Data Engineering/ Data Science:
- Familiarity with operationalizing ML algorithms into production business processes: e.g., experience with containerization (such as Docker, Kubernetes, or Open Shift), competency with MLOps tools (such as Kubeflow, MLflow, Seldon, or Paperspace/Gradient);
- Familiarity with designing, building, and deploying production-level data pipelines using tools from Hadoop stack. Comfortable developing applications that make use of Hive/Impala, HBase, Oozie, Spark, NiFi, Apache Beam, Apache Airflow etc.;
 -Some experience in the following Big Data frameworks: File Format (Parquet, AVRO, ORC), Resource Management, Distributed Processing;
Technical Expertise:
- Familiarity with MS Azure, Amazon Web Services (AWS), GCP or another public cloud service;
- Some experience/knowledge in at least one scripting language (Python, Perl, JavaScript);
- Some experience implementing open-source frameworks &amp; exposure to various open source &amp; package software architectures (AngularJS, ReactJS, Node, Elastic Search, Spark, Scala, Splunk, Apigee, and Jenkins etc.).
- Some experience with various NoSQL databases (Hive, MongoDB, Couchbase, Cassandra, and Neo4j) will be a plus


**Responsibilities:**
- Scale customer data science workloads and implement new pipelines;
- Work directly with data scientists, product owners and customers to integrate models with business processes;
- Deploy and operationalize ML models:
- Model hyperparameter optimization;
- Model training and automated retraining;
- Model workflows onboarding, integration, monitoring, and decommissioning;
- Model version tracking and governance;
- Model drift monitoring.
- Transform complex analytical models in scalable, production-ready solutions;
- Triage, support, resolve and automate anomaly detection for enterprise scale machine learning model deployments.


**We offer:**
- Competitive compensation based on your skills, experience, and customer satisfaction;
- Opportunity to work on challenging and exciting international projects;
- Flexible working hours and the possibility to work remotely when needed;
 -Regular performance evaluation twice a year;
- Long-term contract with 20-25 paid time off working days (for vacation, sick, and personal leave);
- Corporate English courses from A1 to C1 level and monthly English-speaking clubs;
- Compensation of professional conference attendance according to the corporate policy;
- Compensation of medical insurance/gym according to the corporate policy;
- Casual, friendly, and family work environment, flat organizational structure;
- Regular knowledge sharing meetups and various corporate events (such as the company’s Birthday celebration and summer family party);
- Newborn and wedding bonuses;
- Gameroom with a lounge zone, PlayStation, and sports equipment;
- Travel and visa assistance for employees;
- Coffee, cookies, nuts, and dried fruits for a productive day;
- Friday brunches with fresh bakery;
- Yoga lessons;
- Secure bike storage (Odessa).