Logo
  • Publica Anunt
  • Cauta Joburi
  • En

LoginIntra in cont

Intra in cont
  • Continut personalizat
  • Solutii si produse de recrutare
Log In Ai uitat parola ?
Inregistrare
Cont nou?
Creeaza-ti cont

Intra in cont

Ai uitat parola ?
Cautare avansata Alerte joburi Avanseaza in cariera Joburi Studenti Adauga CV Alege produs de recrutare

Alerte joburi

Anuntul de job nu mai este valabil. Va prezentam mai jos cateva oferte de angajare similare cu anuntul cautat de dvs.

4 joburi disponibile

Seteaza o alerta de joburi
Refine Search
Cautare curenta
senior big data engineer
WA Consultants
Senior Platform Engineer (GCP)
WA Consultants
Required for a 16-month (hybrid 50/50) contract, a Platform Engineer/Solution Architect for a Swedish-based client. Role: Develop cloud landing zone and governance framework Develop central platform services to streamline developer efficiency, e,g WIF, PAM, Patch Management, etc GCP SME to advise product teams and share best practice Technical Skills Proficiency in Google Cloud Platform (GCP) services such as Compute Engine, Kubernetes Engine, Cloud Storage, BigQuery, Pub/Sub, Dataflow, etc. Proven expertise in designing and implementing scalable, reliable, and secure cloud architectures on GCP. Proficiency in Infrastructure as Code (IaC) tools like Terraform, Deployment Manager, or Cloud Deployment Manager for automating infrastructure provisioning on GCP To arrange a Teams-based interview, please email in the first instance, your CV to: (see below) WA Consultants is an Employment Business and an Employment Agency as described within The Conduct of Employment Agencies and Employment Businesses Regulations 2003.
03/07/2025
Project-based
Required for a 16-month (hybrid 50/50) contract, a Platform Engineer/Solution Architect for a Swedish-based client. Role: Develop cloud landing zone and governance framework Develop central platform services to streamline developer efficiency, e,g WIF, PAM, Patch Management, etc GCP SME to advise product teams and share best practice Technical Skills Proficiency in Google Cloud Platform (GCP) services such as Compute Engine, Kubernetes Engine, Cloud Storage, BigQuery, Pub/Sub, Dataflow, etc. Proven expertise in designing and implementing scalable, reliable, and secure cloud architectures on GCP. Proficiency in Infrastructure as Code (IaC) tools like Terraform, Deployment Manager, or Cloud Deployment Manager for automating infrastructure provisioning on GCP To arrange a Teams-based interview, please email in the first instance, your CV to: (see below) WA Consultants is an Employment Business and an Employment Agency as described within The Conduct of Employment Agencies and Employment Businesses Regulations 2003.
Joseph Harry Ltd
Senior Software Engineer Java Kafka AWS Finance New York
Joseph Harry Ltd Manhattan, New York
Senior Java Software Engineer (Developer Programmer Java Software Engineer Python Senior Data Lake Datalake Data Mesh Fabric Apache Kafka Spark Apache Iceberg Big Data Agile Buy Side Asset Manager Investment Management Banking Finance Front Office Front Office Trading Financial Services) required by our trading software client in Manhattan, New York City. You MUST have the following: Experience as Senior Java Developer/Software Engineer Expert level Java Java 17 or more recent AWS Good design ability- taking requirements and specification and turning them into technical designs to deliver Kafka Some Python ability Experience working in an enterprise-scale environment The following is DESIRABLE, not essential: Spark Role: Senior Java Software Engineer (Developer Programmer Java Software Engineer Python Senior Data Lake Datalake Data Mesh Fabric Apache Kafka Spark Apache Iceberg Big Data Agile Buy Side Asset Manager Investment Management Banking Finance Front Office Front Office Trading Financial Services) required by our trading software client in Manhattan, New York City. You will be a senior member of a ten-person team, mostly based in New York, that are responsible for an AWS-based data lake. You will be an escalation point for production issues but, in the next few months, play a significant part in the migration of this data lake to a data mesh architecture. For this, you will need to possess good design skills, Java 17+, AWS, Kafka and Python. You do not need experience with data mesh architectures or Apache Iceberg, which they will be using. However, you will need to have operated at enterprise-scale environments. This is an environment of petabytes of data. The company has hybrid working with 3 days/week in the office. This is compulsory. Salary and Comp: $180k - $240k + 40% Bonus + 401k
02/07/2025
Full time
Senior Java Software Engineer (Developer Programmer Java Software Engineer Python Senior Data Lake Datalake Data Mesh Fabric Apache Kafka Spark Apache Iceberg Big Data Agile Buy Side Asset Manager Investment Management Banking Finance Front Office Front Office Trading Financial Services) required by our trading software client in Manhattan, New York City. You MUST have the following: Experience as Senior Java Developer/Software Engineer Expert level Java Java 17 or more recent AWS Good design ability- taking requirements and specification and turning them into technical designs to deliver Kafka Some Python ability Experience working in an enterprise-scale environment The following is DESIRABLE, not essential: Spark Role: Senior Java Software Engineer (Developer Programmer Java Software Engineer Python Senior Data Lake Datalake Data Mesh Fabric Apache Kafka Spark Apache Iceberg Big Data Agile Buy Side Asset Manager Investment Management Banking Finance Front Office Front Office Trading Financial Services) required by our trading software client in Manhattan, New York City. You will be a senior member of a ten-person team, mostly based in New York, that are responsible for an AWS-based data lake. You will be an escalation point for production issues but, in the next few months, play a significant part in the migration of this data lake to a data mesh architecture. For this, you will need to possess good design skills, Java 17+, AWS, Kafka and Python. You do not need experience with data mesh architectures or Apache Iceberg, which they will be using. However, you will need to have operated at enterprise-scale environments. This is an environment of petabytes of data. The company has hybrid working with 3 days/week in the office. This is compulsory. Salary and Comp: $180k - $240k + 40% Bonus + 401k
Head of AI
scrumconnect ltd
Role Overview As Head of AI, you will be the primary technical driver of all AI/ML initiatives. You'll report directly to the CEO/CTO and own the full life cycle of our AI roadmap-from research and proof-of-concept to scalable production. We're looking for a doer who can rapidly prototype models, optimize for performance, and mentor junior engineers, all while helping define product strategy. In this role, you will: Lead AI strategy and execution in a high-ambiguity environment. Build, train, and deploy state-of-the-art models (eg, deep learning, NLP, computer vision, reinforcement learning, or relevant domain-specific architectures). Design infrastructure for data ingestion, annotation, experimentation, model versioning, and monitoring. Collaborate closely with product, design, and DevOps to integrate AI features into our platform. Continuously evaluate new research, open-source tools, and emerging frameworks to keep us at the forefront. Recruit, mentor, and grow an AI/ML team as we scale beyond our seed round. Key Responsibilities 1. Architecture & Hands-On Development Define and implement end-to-end AI pipelines: data collection/cleaning, feature engineering, model training, validation, and inference. Rapidly prototype novel models (eg, neural networks, probabilistic models) using PyTorch, TensorFlow, JAX, or equivalent. Productionize models in cloud/on-prem environments (AWS/GCP/Azure) with containerization (Docker/Kubernetes) and ensure low-latency, high-availability inference. 2. Strategic Leadership Develop a multi-quarter AI roadmap aligned with product milestones and fundraising milestones. Identify and evaluate opportunities for AI-driven competitive advantages (eg, proprietary data, unique model architectures, transfer/few-shot learning). Collaborate with business stakeholders to translate big problems into technically feasible AI solutions. 3. Data & Infrastructure Oversee the creation and maintenance of scalable data pipelines (ETL/ELT) and data lakes/warehouses. Establish best practices for data labeling, versioning, and governance to ensure high data quality. Implement ML Ops processes: CI/CD for model training, automated testing, model-drift detection, and continuous monitoring. 4. Team Building & Mentorship Hire and mentor AI/ML engineers, data scientists, and research interns. Set coding standards, model-development guidelines, and rigor around reproducible experiments (eg, clear Git workflow, experiment tracking). Conduct regular code/model reviews and foster a culture of learn by doing and iterative improvement. 5. Research & Innovation Stay abreast of state-of-the-art AI research (eg, pre-training, fine-tuning, generative methods) and evaluate applicability. Publish or present whitepapers/prototype demos if appropriate (keeping stealth constraints in mind). Forge partnerships with academic labs or open-source communities to accelerate innovation. Minimum Qualifications Experience (7 + years total; 3 + years in senior/lead role): Demonstrated track record of shipping AI/ML products end-to-end (from prototype to production). Hands-on expertise building and deploying deep learning models (eg, CNNs, Transformers, graph neural networks) in real-world applications. Proficiency in Python and core ML libraries (PyTorch, TensorFlow, scikit-learn, Hugging Face, etc.). Strong software engineering background: data structures, algorithms, distributed systems, and version control (Git). Experience designing scalable ML infrastructure on cloud platforms (AWS SageMaker, GCP AI Platform, Azure ML, or equivalent). Solid understanding of data-engineering concepts: SQL/noSQL, data pipelines (Airflow, Prefect, or similar), and batch/streaming frameworks (Spark, Kafka). Leadership & Communication: Proven ability to lead cross-functional teams in ambiguous startup settings. Exceptional written and verbal communication skills-able to explain complex concepts to both technical and non-technical stakeholders. Experience recruiting and mentoring engineers or data scientists in a fast-paced environment. Education: Bachelor's or Master's in Computer Science, AI/ML, Electrical Engineering, Statistics, or a related field. (Ph.D. in AI/ML is a plus but not required if hands-on experience is extensive.) Preferred (Nice-to-Have) Prior experience in a stealth-mode or early-stage startup, ideally taking an AI product from 0 - 1. Background in a relevant domain (eg, healthcare AI, autonomous systems, finance, robotics, computer vision, or NLP). Hands-on experience with large-scale language models (LLMs) and prompt engineering (eg, GPT, BERT, T5 family). Familiarity with on-device or edge-AI deployments (eg, TensorFlow Lite, ONNX, mobile/Embedded inference). Knowledge of MLOps tooling (MLflow, Weights & Biases, Kubeflow, or similar) for experiment tracking and model governance. Open-source contributions or published papers in top-tier AI/ML conferences (NeurIPS, ICML, CVPR, ACL, etc.). Soft Skills & Cultural Fit Doer Mindset: You thrive in scrappy, ambiguous environments. You'll roll up your sleeves to write production code, prototype research ideas, and iterate quickly. Bias for Action: You favor shipping an MVP quickly, measuring impact, and iterating-over striving for perfect academic proofs that never see production. Ownership Mentality: You treat the startup as your own: you take responsibility for system uptime, data integrity, and feature adoption, not just model accuracy. Collaborative Attitude: You value cross-functional teamwork and can pivot between researcher mode and software engineer mode depending on the task at hand. Growth-Oriented: You continually learn new algorithms, architectures, and engineering best practices; you encourage team members to do the same. What We Offer Equity Package: Meaningful ownership stake, commensurate with an early leadership role. Competitive Compensation: Salary aligned with early-stage startup benchmarks; a large portion of the upside is in equity. Autonomy & Impact: You'll shape the technical direction of our AI stack and lay the groundwork for a market-leading product. Flexible Work Environment: Remote-friendly with occasional in-person retreats or team meetups. Learning Budget: Funds for conferences, courses, or publications to ensure you stay at the bleeding edge. Fast-Track Growth: As our first AI hire and eventual team leader, you'll rapidly expand your responsibilities-and the team you build-within months. How to Apply Please send your resume/CV and a brief cover letter with the subject line: Head of AI Application - [Your Name] In your cover letter, highlight: 1. A recent project where you built and deployed an AI/ML system end-to-end (include technical stack and impact). 2. Any leadership or mentoring experience guiding other engineers or data scientists. 3. Why you're excited to join a stealth startup and move quickly from prototype to production. We will review applications on a rolling basis and aim to schedule initial calls within two weeks of receipt. Equal Opportunity: We are committed to building a diverse team and welcome applicants of all backgrounds. We celebrate differences and encourage individuals who thrive in a fast-paced, collaborative, and impact-driven culture to apply. Ready to build world-class AI from day one? Come join us and help shape the future.
01/07/2025
Full time
Role Overview As Head of AI, you will be the primary technical driver of all AI/ML initiatives. You'll report directly to the CEO/CTO and own the full life cycle of our AI roadmap-from research and proof-of-concept to scalable production. We're looking for a doer who can rapidly prototype models, optimize for performance, and mentor junior engineers, all while helping define product strategy. In this role, you will: Lead AI strategy and execution in a high-ambiguity environment. Build, train, and deploy state-of-the-art models (eg, deep learning, NLP, computer vision, reinforcement learning, or relevant domain-specific architectures). Design infrastructure for data ingestion, annotation, experimentation, model versioning, and monitoring. Collaborate closely with product, design, and DevOps to integrate AI features into our platform. Continuously evaluate new research, open-source tools, and emerging frameworks to keep us at the forefront. Recruit, mentor, and grow an AI/ML team as we scale beyond our seed round. Key Responsibilities 1. Architecture & Hands-On Development Define and implement end-to-end AI pipelines: data collection/cleaning, feature engineering, model training, validation, and inference. Rapidly prototype novel models (eg, neural networks, probabilistic models) using PyTorch, TensorFlow, JAX, or equivalent. Productionize models in cloud/on-prem environments (AWS/GCP/Azure) with containerization (Docker/Kubernetes) and ensure low-latency, high-availability inference. 2. Strategic Leadership Develop a multi-quarter AI roadmap aligned with product milestones and fundraising milestones. Identify and evaluate opportunities for AI-driven competitive advantages (eg, proprietary data, unique model architectures, transfer/few-shot learning). Collaborate with business stakeholders to translate big problems into technically feasible AI solutions. 3. Data & Infrastructure Oversee the creation and maintenance of scalable data pipelines (ETL/ELT) and data lakes/warehouses. Establish best practices for data labeling, versioning, and governance to ensure high data quality. Implement ML Ops processes: CI/CD for model training, automated testing, model-drift detection, and continuous monitoring. 4. Team Building & Mentorship Hire and mentor AI/ML engineers, data scientists, and research interns. Set coding standards, model-development guidelines, and rigor around reproducible experiments (eg, clear Git workflow, experiment tracking). Conduct regular code/model reviews and foster a culture of learn by doing and iterative improvement. 5. Research & Innovation Stay abreast of state-of-the-art AI research (eg, pre-training, fine-tuning, generative methods) and evaluate applicability. Publish or present whitepapers/prototype demos if appropriate (keeping stealth constraints in mind). Forge partnerships with academic labs or open-source communities to accelerate innovation. Minimum Qualifications Experience (7 + years total; 3 + years in senior/lead role): Demonstrated track record of shipping AI/ML products end-to-end (from prototype to production). Hands-on expertise building and deploying deep learning models (eg, CNNs, Transformers, graph neural networks) in real-world applications. Proficiency in Python and core ML libraries (PyTorch, TensorFlow, scikit-learn, Hugging Face, etc.). Strong software engineering background: data structures, algorithms, distributed systems, and version control (Git). Experience designing scalable ML infrastructure on cloud platforms (AWS SageMaker, GCP AI Platform, Azure ML, or equivalent). Solid understanding of data-engineering concepts: SQL/noSQL, data pipelines (Airflow, Prefect, or similar), and batch/streaming frameworks (Spark, Kafka). Leadership & Communication: Proven ability to lead cross-functional teams in ambiguous startup settings. Exceptional written and verbal communication skills-able to explain complex concepts to both technical and non-technical stakeholders. Experience recruiting and mentoring engineers or data scientists in a fast-paced environment. Education: Bachelor's or Master's in Computer Science, AI/ML, Electrical Engineering, Statistics, or a related field. (Ph.D. in AI/ML is a plus but not required if hands-on experience is extensive.) Preferred (Nice-to-Have) Prior experience in a stealth-mode or early-stage startup, ideally taking an AI product from 0 - 1. Background in a relevant domain (eg, healthcare AI, autonomous systems, finance, robotics, computer vision, or NLP). Hands-on experience with large-scale language models (LLMs) and prompt engineering (eg, GPT, BERT, T5 family). Familiarity with on-device or edge-AI deployments (eg, TensorFlow Lite, ONNX, mobile/Embedded inference). Knowledge of MLOps tooling (MLflow, Weights & Biases, Kubeflow, or similar) for experiment tracking and model governance. Open-source contributions or published papers in top-tier AI/ML conferences (NeurIPS, ICML, CVPR, ACL, etc.). Soft Skills & Cultural Fit Doer Mindset: You thrive in scrappy, ambiguous environments. You'll roll up your sleeves to write production code, prototype research ideas, and iterate quickly. Bias for Action: You favor shipping an MVP quickly, measuring impact, and iterating-over striving for perfect academic proofs that never see production. Ownership Mentality: You treat the startup as your own: you take responsibility for system uptime, data integrity, and feature adoption, not just model accuracy. Collaborative Attitude: You value cross-functional teamwork and can pivot between researcher mode and software engineer mode depending on the task at hand. Growth-Oriented: You continually learn new algorithms, architectures, and engineering best practices; you encourage team members to do the same. What We Offer Equity Package: Meaningful ownership stake, commensurate with an early leadership role. Competitive Compensation: Salary aligned with early-stage startup benchmarks; a large portion of the upside is in equity. Autonomy & Impact: You'll shape the technical direction of our AI stack and lay the groundwork for a market-leading product. Flexible Work Environment: Remote-friendly with occasional in-person retreats or team meetups. Learning Budget: Funds for conferences, courses, or publications to ensure you stay at the bleeding edge. Fast-Track Growth: As our first AI hire and eventual team leader, you'll rapidly expand your responsibilities-and the team you build-within months. How to Apply Please send your resume/CV and a brief cover letter with the subject line: Head of AI Application - [Your Name] In your cover letter, highlight: 1. A recent project where you built and deployed an AI/ML system end-to-end (include technical stack and impact). 2. Any leadership or mentoring experience guiding other engineers or data scientists. 3. Why you're excited to join a stealth startup and move quickly from prototype to production. We will review applications on a rolling basis and aim to schedule initial calls within two weeks of receipt. Equal Opportunity: We are committed to building a diverse team and welcome applicants of all backgrounds. We celebrate differences and encourage individuals who thrive in a fast-paced, collaborative, and impact-driven culture to apply. Ready to build world-class AI from day one? Come join us and help shape the future.
Empiric Solutions
New Contract opportunity - Advanced SCALA - Netherlands
Empiric Solutions Amsterdam, Noord-Holland
New Contract opportunity - SCALA - Netherlands We are looking for an experienced and highly capable Senior SCALA Engineer Role Description: MongoDB and Parquet, including knowledge about data modelling. Familiarity with Google Cloud services: Big Query and Storage. Familiarity with fundamental data science concepts. Must Have Skills: Scala (Advanced level) and Shell Scripting experience. SQL, including writing and optimizing complex queries. Infrastructure as Code: Experience Scripting infrastructure changes using Terraform. Desirable Skills: Python (nice to have). Experience with Apache Spark Structured Streaming and Hadoop. Experience with MongoDB and Parquet, including a solid understanding of data modelling. Strong expertise in Apache Kafka. For a confidential chat to explore this opportunity, please apply below and submit your CV.
30/06/2025
Project-based
New Contract opportunity - SCALA - Netherlands We are looking for an experienced and highly capable Senior SCALA Engineer Role Description: MongoDB and Parquet, including knowledge about data modelling. Familiarity with Google Cloud services: Big Query and Storage. Familiarity with fundamental data science concepts. Must Have Skills: Scala (Advanced level) and Shell Scripting experience. SQL, including writing and optimizing complex queries. Infrastructure as Code: Experience Scripting infrastructure changes using Terraform. Desirable Skills: Python (nice to have). Experience with Apache Spark Structured Streaming and Hadoop. Experience with MongoDB and Parquet, including a solid understanding of data modelling. Strong expertise in Apache Kafka. For a confidential chat to explore this opportunity, please apply below and submit your CV.

Modal Window

Cauta joburi dupa:
  • Domeniu:
  • IT_Software Development
  • Bănci
  • Vanzari
  • Medical
  • Inginerie
  • Orase:
  • Bucuresti
  • Cluj-Napoca
  • Timisoara
  • Iasi
  • Constanta
  • Craiova
  • Brasov
  • Galati
  • Ploiesti
  • Oradea
  • Pitesti
  • Sibiu
Helpful Resources
  • Blog Cariera
  • Produse de recrutare
  • Contact
Servicii angajatori
  • Publicare anunturi
  • Administrare Aplicatii
  • Cauta CV-uri
Instrumente candidati
  • Joburi Studenti
  • Alerte joburi
  • Administrare Aplicatii
  • Adauga CV
Joburi internationale
  • Jobs in US
  • Jobs in UK
  • Offres d'emploi en France
  • Jobs in Deutschland

© All rights reserved. Copyrights @Carieranoua

  • Despre noi
  • Companii
  • Termeni si conditii
  • Confidentialitate
  • Contact