Search Machine Learning Research Engineer Job at Perplexity (Berlin)

Machine Learning Research Engineer

Internship program: 12 - 24 weeks, full-time, in-person in the Berlin office.

Location

Germany , Berlin

Salary:

Not provided

Perplexity

Expiration Date

Until further notice

Requirements

Understanding of search and retrieval systems, including quality evaluation principles and metrics
Strong proficiency with PyTorch, including experience in distributed training techniques and performance optimization for large models
Interested in representation learning, including contrastive learning, dense & sparse vector representations, representation fusion, cross-lingual representation alignment, training data optimization and robust evaluation
Publication record in AI/ML conferences or workshops (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, SIGIR)

Job Responsibility

Relentlessly push search quality forward — through models, data, tools, or any other leverage available
Train, and optimize large-scale deep learning models using frameworks like PyTorch, leveraging distributed training (e.g., PyTorch Distributed, DeepSpeed, FSDP) and hardware acceleration, with a focus on retrieval and ranking models
Conduct research in representation learning, including contrastive learning, multilingual, evaluation, and multimodal modeling for search and retrieval
Build and optimize RAG pipelines for grounding and answer generation

Fulltime

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

Machine Learning Engineer

Location

United States , Los Angeles

Salary:

Not provided

Robert Half

Expiration Date

Until further notice

Requirements

Lead the design, implementation, and ongoing maintenance of scalable ML infrastructure on Databricks, including ML flow for experiment tracking, model registry, and model serving endpoints
Oversee the development of the ML Ops platform and automated pipelines for deploying, monitoring, and maintaining models within production environments
Implement robust solutions for model versioning, systematic retraining, and comprehensive artifact management using Databricks Unity Catalog for ML governance
Design and manage Databricks Feature Store for consistent feature engineering across training and inference pipelines
Architect and implement Retrieval-Augmented Generation (RAG) systems for document Q&A, enabling business teams to query fund documents, investor letters, and market research
Design, deploy, and manage vector database solutions (Databricks Vector Search, Pinecone, or similar) for semantic search and retrieval across enterprise documents
Lead LLM fine-tuning and customization initiatives, training models like Claude or open-source alternatives with CIM proprietary data while ensuring data privacy and compliance
Develop and optimize document processing pipelines including PDF parsing, chunking strategies, and embedding generation for RAG applications
Implement prompt engineering best practices and LLM evaluation frameworks to ensure output quality, relevance, and factual accuracy
Build guardrails and safety measures for GenAI applications, including hallucination detection, output validation, and source attribution

Job Responsibility

ML Model Deployment & Platform Management
Generative AI & LLM Operations
Automation & CI/CD Pipelines

What we offer

medical
vision
dental
life and disability insurance
401(k) plan

Machine Learning Engineer

As an ML Engineer you’ll play a crucial role in advancing our shared mission of ...

Location

Germany; Netherlands; France; Serbia; Kazakhstan; Armenia; Finland; United Kingdom , Berlin; Amsterdam; Helsinki; London

Salary:

Not provided

Corsearch

Expiration Date

Until further notice

Requirements

Proven experience as a Machine Learning Engineer with at least 3 years of professional experience
Strong proficiency in machine learning frameworks such as CatBoost, TensorFlow, PyTorch, or Keras
Experience with image processing, feature extraction, and text preprocessing techniques
Solid understanding of algorithms for tasks such as object detection, image classification, text extraction, and sentiment analysis
Hands-on experience with large datasets and data pipelines for training and deploying ML models
Strong analytical and problem-solving skills, with the ability to translate business challenges into technical solutions
Full professional English proficiency

Job Responsibility

Develop and optimize machine learning models with a focus on computer vision (e.g., image recognition, object detection) and NLP (e.g., text classification, sentiment analysis, entity recognition)
Train and fine-tune deep learning models (e.g., CNNs, RNNs, Transformers) for tasks such as reverse image search, image-text matching, and online content analysis
Collaborate with cross-functional teams to improve product and system performance
Research and implement state-of-the-art algorithms and techniques to improve the accuracy and performance of AI solutions
Build scalable data pipelines for the ingestion and processing of image and text data for model training and evaluation
Continuously monitor the performance of models in production, identify bottlenecks, and propose optimizations

Fulltime

Senior Machine Learning Engineer

Reddit is a community of communities. It’s built on shared interests, passion, a...

Location

United States , Remote

Salary:

216700.00 - 303400.00 USD / Year

Expiration Date

Until further notice

Requirements

3-5+ years of experience building, deploying, and operating machine learning systems in production
Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals
ML Fundamentals: a strong grasp of algorithms, from classic statistical learning (XGBoost, Random Forests, regressions) to DL architectures (Transformers, CNNs, GNNs)
Hands-on experience with modern ML frameworks (e.g., PyTorch, TensorFlow)
Experience designing scalable ML pipelines, data processing systems, and model serving infrastructure
Ability to work cross-functionally and translate ambiguous product or business problems into technical solutions
Experience improving measurable metrics through applied machine learning

Job Responsibility

Design, build, and deploy production-grade machine learning models and systems at scale
Own the full ML lifecycle: from problem definition and feature engineering to training, evaluation, deployment, and monitoring
Build scalable data and model pipelines with strong reliability, observability, and automated retraining
Work with large-scale datasets to improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems
Partner cross-functionally with Product, Data Science, Infrastructure, and Engineering teams to translate complex problems into ML solutions
Improve system performance across latency, throughput, and model quality metrics
Research and apply state-of-the-art machine learning and AI techniques, including deep learning, graph & transformers based, and LLM evaluation/alignment
Contribute to technical strategy, architecture, and long-term ML roadmap

What we offer

Comprehensive Healthcare Benefits and Income Replacement Programs
401k with Employer Match
Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
Family Planning Support
Gender-Affirming Care
Mental Health & Coaching Benefits
Flexible Vacation & Paid Volunteer Time Off
Generous Paid Parental Leave
Medical, dental, and vision insurance

Fulltime

Senior Machine Learning Engineer

Reddit is a community of communities. It’s built on shared interests, passion, a...

Location

Canada , Ontario

Salary:

Not provided

Expiration Date

Until further notice

Requirements

3-5+ years of experience building, deploying, and operating machine learning systems in production
Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals
ML Fundamentals: a strong grasp of algorithms, from classic statistical learning (XGBoost, Random Forests, regressions) to DL architectures (Transformers, CNNs, GNNs)
Hands-on experience with modern ML frameworks (e.g., PyTorch, TensorFlow)
Experience designing scalable ML pipelines, data processing systems, and model serving infrastructure
Ability to work cross-functionally and translate ambiguous product or business problems into technical solutions
Experience improving measurable metrics through applied machine learning

Job Responsibility

Design and build production ML systems that power core experiences across the platform, including: Personalized recommendations, search, and ranking systems
Intelligent advertising systems including ranking, bidding, measurement, and optimization
Content, Advertisers, and User understanding
Large-scale machine learning pipelines, model serving infrastructure, and real-time decision systems
Applied AI and LLM-driven experiences
Design, build, and deploy production-grade machine learning models and systems at scale
Own the full ML lifecycle
Build scalable data and model pipelines
Work with large-scale datasets to improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems
Partner cross-functionally with Product, Data Science, Infrastructure, and Engineering teams

What we offer

Comprehensive Healthcare Benefits and Income Replacement Programs
401k with Employer Match
Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
Family Planning Support
Gender-Affirming Care
Mental Health & Coaching Benefits
Flexible Vacation & Paid Volunteer Time Off
Generous Paid Parental Leave

Fulltime

Senior Machine Learning Engineer

As Microsoft continues to push the boundaries of AI, we are on the lookout for p...

Location

United States , Mountain View

Salary:

119800.00 - 258000.00 USD / Year

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.

Job Responsibility

Build and Deploy Models: Design, train, evaluate, and deploy machine learning models for natural language understanding tasks including intent detection, topic classification, conversation summarization, and user personas
Design ML Pipelines: Architect scalable, production-grade training and inference pipelines using Spark, Databricks, Azure ML and modern ML frameworks
NLP and Representation Learning: Develop and fine-tune transformer-based models and text encoders
build and maintain embedding pipelines and vector databases for semantic search and retrieval
Experimentation and Evaluation: Drive rigorous offline and online experimentation to measure model quality, iterate on architectures, and improve key product metrics
Collaborate Across Teams: Partner with data engineers, data scientists, and product teams to translate research insights into shipped features and align model outputs with product goals
Show Ownership Mindset: Proactively monitor model performance in production, diagnose regressions, and address scalability and reliability challenges before they become bottlenecks
Contribute Strategically: Identify opportunities to improve model architectures, training methodologies, and evaluation frameworks
mentor others on ML best practices

What we offer

Certain roles may be eligible for benefits and other compensation

Fulltime

Machine Learning Engineer

As a Machine Learning Engineer at Mercor, you’ll operate at the intersection of ...

Location

United States , San Francisco

Salary:

130000.00 USD / Year

Mercor

Expiration Date

Until further notice

Requirements

Strong backend engineering skills (ex. Python/Django or similar) plus a solid foundation in applied ML and statistics
Proven experience shipping production systems or ML-driven products end-to-end
High ownership and comfort operating in ambiguous, fast-changing environments
Generalist mindset: willing to flex between backend, modeling, data pipelines, and product problem-solving

Job Responsibility

Research, train, and productionize ML models for engagement prediction, scoring, search
Build backend infrastructure and APIs to serve ML models reliably at scale
Run experiments, analyze results, and iterate quickly to improve both models and product performance
Work cross-functionally with Operations and Product to translate business needs into model-driven solutions
Wear many hats: from backend engineer to applied ML practitioner to product problem-solver

What we offer

Generous equity grant vested over 4 years
A $20K relocation bonus (if moving to the Bay Area)
A $10K housing bonus (if you live within 0.5 miles of our office)
A $1K monthly stipend for meals
Free Equinox membership
Health insurance

Fulltime

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