136 applicants

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Company

Original Job Post

Reflex Media, Inc · 6 days ago

Machine Learning Engineer

Las Vegas, NV

Full-time

Hybrid

Mid Level

3+ years exp

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Responsibilities

Collaborate with data scientists, product and marketing teams, translating business needs into technical specifications for ML solutions.

Develop machine learning models and algorithms.

Evaluate, tune, and iterate models until desired effectiveness is achieved (targeted precision, F1, type-II error rates, etc.).

Assist in overall architecture design, model deployment, and integration with existing systems.

Optimize ML model deployments for performance and scalability, ensuring they operate efficiently within production environments.

Optimize cost in training schemes, deployment options, and inference endpoints.

Implement automated processes for data preparation, model training, testing, and deployment.

Consult with development, product, and marketing teams regarding data collection requirements.

Monitor and maintain ML systems, addressing any issues to ensure they deliver consistent, reliable performance.

Stay up-to-date with ML technologies and methodologies advancements, incorporating best practices into our projects.

Qualification

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Machine learningPythonSqlLinuxMl frameworksSoftware engineeringCloud computingCicdData analysisStatistical knowledgeProblem-solvingCommunicationCollaborationSelf-starterSystem IntegrationRecommended SystemsEnsemble MethodsLLMsRAG-based SystemsAWS ServicesSagemakerAPI GatewayLambdaRedshiftRedshift SpectrumECREC2S3DynamoDBCloudwatch

Required

Bachelor’s degree in Computer Science, Engineering, Statistics, or related technical field.

Three years’ proven experience as an effective ML Engineer, Data Engineer, Data Scientist, or similar technical role.

Demonstrable working experience in ML model building, iteration, evaluation, retraining, and maintenance (re-evaluation, etc.).

In-depth knowledge of machine learning model development lifecycles.

Strong programming skills (Python preferred).

Strong database experience (advanced SQL skills a must).

Working experience with Linux servers, BASH, and process management.

Working experience using ML frameworks (PyTorch, Tensorflow, Huggingface, Transformers, LangChain, etc.).

Demonstrable experience with software engineering tools and best practices (version control, writing extensible code, contributing to and maintaining a shared codebase, containerization, etc.).

Working experience with cloud computing platforms and services (AWS preferred).

Knowledge of CICD best practices and tooling (automated testing and deployment pipelines, etc.)

Solid data-related judgment - has a “nose” for data correctness, knowledge of dataset biases and how to correct for them, etc.

Strong statistical knowledge and analytical skills.

Self-starter - unafraid to make decisions and take risks.

Excellent problem-solving abilities and strong communication skills, capable of collaborating effectively with cross-functional teams.

Desire to work in a fast-paced and results-driven environment where personal contribution can immediately translate into real business impact.

Preferred

Master’s Degree or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or related technical field.

Portfolio of projects demonstrating expertise in machine learning, data analysis, and/or system integration.

Working experience with recommended systems, ensemble methods, LLMs, and/or RAG-based systems.

In-depth working experience with specific AWS services (Sagemaker, API Gateway, Lambda, Redshift, Redshift Spectrum, ECR, EC2, S3, DynamoDB, Cloudwatch)

API maintenance and development experience.

Micro-services management and development experience.