Search Machine Learning Engineer Intern Job at Perplexity (Belgrade)

Machine Learning Engineer

We are looking for a Machine Learning Engineer to build and support production-r...

Location

United States , Los Angeles

Salary:

Not provided

Robert Half

Expiration Date

Until further notice

Requirements

5+ years of experience in machine learning engineering, MLOps, or a closely related technical role
Strong proficiency in Python and practical experience building machine learning solutions in production environments
Hands-on expertise with Databricks and familiarity with capabilities such as experiment tracking, model governance, workflows, and feature management
Experience deploying and maintaining generative AI or large language model applications, including retrieval-based architectures and vector databases
Solid understanding of automation, CI/CD practices, and workflow orchestration for data and model pipelines
Background working with machine learning frameworks such as TensorFlow and applying AI techniques in real-world business settings
Knowledge of model evaluation, monitoring, and governance practices with attention to reliability, compliance, and traceability

Job Responsibility

Build and maintain scalable machine learning infrastructure in Databricks, including experiment tracking, model management, and serving capabilities for production use
Create and improve MLOps frameworks and automated deployment pipelines that support model release, monitoring, and lifecycle management
Establish disciplined processes for model version control, retraining, and artifact governance using tools such as Unity Catalog
Develop and administer a feature store strategy that keeps training and inference data consistent across machine learning workflows
Design retrieval-augmented generation solutions that allow internal teams to search and interact with documents such as fund materials, investor communications, and research content
Implement and manage vector search platforms to support semantic retrieval across large collections of enterprise documents
Customize and fine-tune large language models using proprietary datasets while protecting data privacy and meeting compliance expectations
Build document ingestion and transformation pipelines that handle parsing, segmentation, and embedding creation for generative AI applications
Introduce prompt design standards, evaluation methods, and application safeguards to improve response quality, reduce hallucinations, and provide source-backed outputs
Automate training, testing, orchestration, and deployment workflows through CI/CD pipelines and tools such as Databricks Workflows, GitHub Actions, Azure DevOps, Airflow, or Prefect

What we offer

Medical, vision, dental, and life and disability insurance
Company 401(k) plan

Staff Artificial Intelligence Machine Learning Engineer

The Role: General Motors is seeking a Staff AI/ML Engineer for the Vehicle Mech...

Location

United States , Austin

Salary:

Not provided

General Motors

Expiration Date

Until further notice

Requirements

Graduate degree (Master's or PhD) in Computer Science, Data Science, Machine Learning, Statistics, Engineering, or a closely related quantitative field
7+ years of hands-on experience designing, building, and operating machine learning systems in production environments
Strong proficiency in Python (production-quality code, testing, packaging) and SQL, with experience working in shared, multi-developer codebases
Practical experience with core ML frameworks such as PyTorch, TensorFlow, or scikit-learn, and with MLOps tooling (e.g., MLflow, CI/CD, model registries, experiment tracking)
Experience building data and ML workloads on cloud platforms, preferably Microsoft Azure, and working with Databricks, Spark, or similar distributed processing frameworks
Demonstrated ability to turn ambiguous real-world problems into shippable AI/ML solutions, owning the details from data exploration through deployed service and ongoing operation
Strong understanding of ML system behavior in production (data issues, non-stationarity, latency, throughput, failure modes) and comfort debugging with logs, metrics, and traces
Excellent communication and collaboration skills, with a track record of influencing decisions and mentoring other AI/ML practitioners

Job Responsibility

Design, build, and operate end-to-end AI/ML solutions (data pipelines, models, services, and tools) for diagnostics, prognostics, and test analytics
Implement production-grade ML pipelines on platforms such as Azure and Databricks, covering data ingestion, feature engineering, training, evaluation, and inference for batch and streaming workloads
Develop and maintain robust, observable ML services and internal tools that make complex vehicle and field data easy to use for engineers and technical stakeholders
Apply practical ML and statistical methods (e.g., tree-based models, time-series and anomaly detection, deep learning where appropriate) with a focus on reliability, explainability, and impact
Own model and data observability in production, including metrics, dashboards, alerts, and remediation workflows for drift, data quality, and performance regressions
Partner with data engineering to define and use industrialized and vectorized data products that support search, RAG, and analytics at scale
Review designs and code, mentor AI/ML practitioners, and help set high standards for testing, logging, deployment, and documentation
Collaborate with diagnostics/prognostics SMEs, validation, safety, and program teams to prioritize work, define success metrics, and embed solutions in day-to-day engineering workflows

Fulltime

Staff Applied Machine Learning Engineer - Intelligent Data, Signals & Systems

As a Staff Applied Machine Learning Engineer focused on Intelligent Data, Signal...

Location

United States , Bay Area

Salary:

276800.00 - 415200.00 USD / Year

Cash App

Expiration Date

Until further notice

Requirements

12+ years building and operating production software and ML systems for business-critical products
Deep expertise in intelligent systems such as ranking/retrieval, recommendations, search, personalization, growth and lifecycle ML, customer intelligence, propensity/churn/LTV, next-best-action, or model-derived risk signals
Strong production ML judgment across feature pipelines, model serving, experimentation, monitoring, feedback loops, online/offline consistency, and reliable signal interfaces
Ability to evaluate impact beyond short-term conversion, including trust, fairness, access, risk, compliance, and long-term engagement
Experience using AI-assisted engineering tools with appropriate verification, testing, and review for customer-impacting systems.

Job Responsibility

Build and operate production ML systems that turn customer and product context into trusted signals, rankings, recommendations, and decision capabilities
Design production data and signal contracts that define intended use, freshness, provenance, confidence, eligibility, and calibration for downstream consumers
Own ranking, retrieval, recommendation, search, propensity, and next-best-action systems end to end, from feature and candidate generation through serving, experimentation, monitoring, and feedback loops
Evaluate customer and business impact beyond short-term conversion, including trust, fairness, access, risk, compliance, long-term engagement, and segment-level performance
Partner across product, growth, data, platform, modeling, risk, and compliance to translate ambiguous goals into measurable ML system designs
Use AI and agents to accelerate development, analysis, testing, documentation, and operations while exposing reusable capabilities to product services, internal tools, and AI-assisted workflows.

What we offer

Remote work
Medical insurance
Flexible time off
Retirement savings plans
Modern family planning

Fulltime

Senior Staff Machine Learning Engineer – Agent Engineering

GEICO is seeking an experienced Sr Staff Machine Learning Engineer – Agent Engin...

Location

United States , New York City; Palo Alto; Chevy Chase

Salary:

130000.00 - 300000.00 USD / Year

Geico

Expiration Date

Until further notice

Requirements

10+ years of professional software development experience with at least two general-purpose programming languages such as Java, C++, Python, TypeScript, etc.
7+ years of experience architecting, building & deploying end-to-end AI solutions utilizing open-source/cloud-agnostic components such as search engine (e.g. elastic search, Qdrant), data warehouse (e.g. snowflake), streaming platform (e.g. Kafka), relational database (e.g. postgresql), Nosql (e.g. Cassandra), distributed processing (e.g. Spark, Ray), workflow orchestration (e.g. Airflow, Temporal), etc.
5+ years’ experience managing end-to-end solution development life cycle, esp. Measurement and monitoring of operations metrics, analytical insights and business outcomes via dashboards and other tools
Bachelor’s degree or above in Computer Science, Engineering, Statistics or a related field

Job Responsibility

Own design, development and maintenance of high-performance AI solutions that utilize agentic workflows to deliver concrete business value for internal stakeholders
Collaborate with cross-functional teams, including data scientists, ML engineers, software engineers, product managers, designers to gather requirements, define project scope and prioritize feature backlogs
Contribute to the selection, evaluation, and implementation of software technologies, tools, and frameworks
Take ownership in project planning and stakeholder management
Mentor and guide junior engineers via code reviews and design sessions

What we offer

Comprehensive Total Rewards program
401K savings plan with 6% match
performance and recognition-based incentives
tuition assistance
mental healthcare
fertility and adoption assistance
workplace flexibility
GEICO Flex program (work from anywhere in the US for up to four weeks per year)

Fulltime

Senior Machine Learning Engineer

We’re looking for a Senior Machine Learning Engineer to lead the design, archite...

Location

United States; Canada; Mexico , San Francisco; Atlanta; Austin; Boston; Chicago; Dallas; Denver; Houston; Jacksonville; Los Angeles; Miami; New York City; Phoenix; Portland; Sacramento; Salt Lake City; San Diego; Seattle; Washington, D.C.; Ottawa; Toronto; Vancouver; Mexico City

Salary:

129500.00 - 230000.00 USD / Year

Scribd

Expiration Date

Until further notice

Requirements

6+ years of experience as a professional ML engineer or software engineer, with a proven track record of delivering production ML systems at scale
Proficiency in at least one key programming language (preferably Python or Golang
Scala or Ruby also considered)
Expertise in designing and architecting large-scale ML pipelines and distributed systems
Deep experience with distributed data processing frameworks (Spark, Databricks, or similar)
Strong cloud expertise (preferably GCP
also AWS and/or Azure) and experience with deployment platforms (ECS, EKS, Lambda)
Experience with embedding-based retrieval, large language models, advanced information retrieval and ranking systems
Experience working with Search systems like query parsing, query intent classification, bm25, reranking, etc.
Proven ability to optimize system performance and make informed trade-offs in ML model and system design

Job Responsibility

Lead complex, cross-team projects from conception to production deployment
Drive technical direction for end-to-end, production-grade ML systems for advanced search capabilities and document understanding
Develop and operate services that power high-traffic pipelines for content discovery and knowledge synthesis
Run large-scale A/B and multivariate experiments to validate models and feature improvements
Mentor other engineers and establish best practices for building scalable, reliable ML systems
Train, evaluate, and deploy ML models (including generative models) to production using Scribd’s internal platform and industry-standard frameworks
Collaborate with engineering and analytics teams to build large-scale ingestion, transformation, and validation pipelines on Databricks
Optimize systems for performance, scalability, and reliability across massive datasets and high-throughput services
Design and run A/B and N-way experiments to measure the impact of model and feature changes
Partner with product managers, data scientists, and analysts to identify opportunities, define requirements, and deliver solutions that solve real user problems

What we offer

Healthcare Insurance Coverage (Medical/Dental/Vision): 100% paid for employees
12 weeks paid parental leave
Short-term/long-term disability plans
401k/RSP matching
Onboarding stipend for home office peripherals + accessories
Learning & Development allowance
Learning & Development programs
Quarterly stipend for Wellness, WiFi, etc.
Mental Health support & resources
Free subscription to the Scribd Inc. suite of products

Fulltime

Machine Learning Engineering Intern

Airbnb is seeking a Machine Learning Engineer Intern for our 2026 Summer Intern ...

Location

United States

Salary:

20.00 - 50.00 USD / Hour

Airbnb

Expiration Date

Until further notice

Requirements

Doctorate students with at least 1 semester of school remaining after the internship (expected graduation after December 2026)
Studying Computer Science or a related field
Knowledge of AI, especially large language model (LLM) fundamentals including fine tuning, data synthesis, reinforcement learning, etc.
Expertise of building large scale ReAct style AI agents
Proficient in Python and other open source LLM libraries like Huggingface
Work authorization for employment in the United States is required

Job Responsibility

Drive a project from end-to-end that aligns with your technical interest and goals
Exploring how new advancements in AI agents can be applied to Airbnb search and discovery experience
Own and drive a capstone project from beginning to end
Collaborate with multiple team members to achieve project milestones
Communicate with stakeholders across different teams to provide project updates
Seek and provide feedback throughout the internship
Actively participate in and contribute to the Engineering org and broader Airbnb community

What we offer

Employee Travel Credits

AI Machine Learning Scientist

Location

United States of America , INDIANAPOLIS

Salary:

Not provided

Elevance Health

Expiration Date

July 15, 2026

Requirements

Bachelor’s degree in a highly quantitative field: Computer Science, Machine Learning, Operational Research, Analytics, Statistics, Mathematics, or a related field of study
Four (4) years of Information Technology (IT) experience, or related experience
Experience with Machine Learning techniques including supervised learning (linear regression and classification) and unsupervised learning (clustering)
Experience with Deep Learning techniques including convolutional neural networks, recurrent neural networks, and reinforcement learning
Experience using Python programming language
Experience with big data technologies including Hadoop, Apache Spark, and AWS
Experience with relational database management and SQL
Experience with Natural Language Processing (NLP) techniques including sentiment analysis and text classification
Experience with statistical analysis and application of statistical methods
Employer will accept a Master’s degree in a highly quantitative field: Computer Science, Machine Learning, Operational Research, Analytics, Statistics, Mathematics, or a related field of study and Two (2) years of Information Technology (IT) experience, or related. Must have the skills listed above.

Job Responsibility

Leverage Artificial Intelligence (AI) scientific and statistical methods to assist with product creation, development, and improvement
Engage with product teams and business stakeholders to align on project objectives and ensure AI models meet business goals
Lead initiatives for developing Machine Learning (ML), Natural Language Processing (NLP), and Large Language Models (LLM) LLM models
Play a critical role in steering the strategic direction for ML, NLP, LLM, and algorithm development within the company’s AI/ML team, collaborating with distinguished experts in AI/ML modeling, ML engineering, data science, and data engineering
Define and articulate roadmaps for AI/ML model development, acting as a key figure in AI-driven transformation to deliver value internally and to customers
Design and develop customized ML, GenAI, NLP, and LLM models for both batch and stream processing-based AI/ML pipelines. This includes handling data ingestion, preprocessing, search and retrieval, Retrieval Augmented Generation (RAG), and ensuring that complete solutions meet all technical and business requirements, as well as Service Level Agreement (SLA) specifications
Work closely with MLOps, machine learning engineers, and software engineers to ensure seamless integration of machine learning models into production systems
Collaborate with the MLOps team to create and maintain strong evaluation solutions and tools that assess model performance, accuracy, consistency, and reliability during development and UAT
Mentor junior team members and influence the strategic direction of our ML and data science projects.

What we offer

merit increases
paid holidays
Paid Time Off
incentive bonus programs
medical
dental
vision
short and long term disability benefits
401(k) +match
stock purchase plan

Fulltime

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Senior Software Engineer, Search

We are looking for a Senior Software Engineer dedicated to the core development ...

Location

Finland , Helsinki

Salary:

Not provided

Aiven Deutschland GmbH

Expiration Date

Until further notice

Requirements

Search Mastery: Deep technical knowledge of OpenSearch or Elasticsearch internals, particularly in resource management, indexing strategies, and query optimization.
Reliability & Operations: A passion for building highly available, resilient distributed systems and a proven track record of solving complex operational challenges.
Hardware: Interest or experience in hardware acceleration, specifically deploying and managing GPU-based instances for data services.
Automation Mindset: Proven experience in designing automated recovery systems and performance-tuning algorithms.
Modern Search Patterns: A strong interest in the evolving landscape, including Vector Database implementations, hybrid search and RAG (Retrieval-Augmented Generation).

Job Responsibility

Autonomic Systems: Design and implement new and improve existing automated management, self-healing recovery mechanisms, and performance-tuning logic for OpenSearch clusters.
Next-Gen Infrastructure: Research, design, and deploy the first GPU-powered instances within the Aiven ecosystem to support intensive search and AI workloads.
AI Node Development: Develop and integrate specialized AI node types to enhance OpenSearch's capability in handling modern machine learning tasks.
Engineering Ownership: Own the health, reliability, and availability metrics of our OpenSearch platform.

What we offer

Participate in Aiven’s equity plan.
Balance work and life with our hybrid work policy.
Choose the equipment you need to set yourself up for success.
Use your Professional Development Plan budget for learning opportunities.
Receive holistic wellbeing support through our global Employee Assistance Program.
Inquire about our Global Time Off Commitment (Parental and Sick Leave, as well as Personal Time)
Enjoy country-specific benefits for our global cast.

Fulltime

Select Country

Search Machine Learning Engineer Intern

Job Description

Job Responsibility

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