{"id":1304551,"url":"https://alion.io/job/pttep-machine-learning-engineer","title":"Machine Learning Engineer","company":{"id":1889562,"name":"PTTEP","domain":"pttep.com","url":"https://alion.io/company/pttep","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bangkok, Thailand"],"countries":["TH"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":32000,"max_usd":85000,"period":"year","method":null,"sample_n":3649},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"BigQuery","optional":false},{"name":"CI/CD","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Kubeflow","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SQL","optional":false},{"name":"XGBoost","optional":false}],"status":"live","first_seen_at":"2026-09-26T12:33:02Z","employer_posted_date":null,"last_verified_at":"2026-09-26T12:33:02Z","board_verified":false,"closed_at":null,"days_open":1,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":1},"description":"Description: Key Accountabilities.\n\nDesign and work on all aspects of bringing ML models into production, develop CI/CD pipelines by collaborating with other disciplines such as data engineering, application development, cloud infrastructure, and security to implement AI solutions in production.\n\nWork collaboratively with data scientists along the machine learning lifecycle from data pipeline, data preparation, model deployment, and model monitoring.\n\nUnderstand and assess AI/ML industry trends to leverage technologies, continuously improve efficiency and effectiveness of the existing algorithms; as well as to understand their impact on our AI/ML solutions.\n\nProvide architectural and technical leadership to drive AI/ML capabilities.\n\nInitiate innovation and development projects to continuously improve the overall efficiency of the team in the engineering aspect.\n\nProfessional Knowledge & Experiences.\n\nDegree in computer science or related fields, with concentration in Machine Learning/AI engineering.\n\nAt least 3 years of experience in implementing and deploying Machine Learning solutions (using various models, such as Linear/Logistic Regression, Support Vector Machines, Neural Networks, etc.). Expertise with Data Science and experience with manipulating/transforming data, model selection, model training, and deployment at scale.\n\nKnowledge and experience in database technologies, such as SQL, NoSQL, and demonstrate knowledge of databases (Google BigQuery preferred), Data ETL framework (Airflow), ML libraries (scikit-learn, XG Boost, PyTorch, etc.), ML Frameworks (Kubeflow, MLFlow, etc.).\n\nKnowledge and experience in Kubernetes technology. Be able to develop CI/CD pipeline, deploy workloads, configure and monitor jobs on kubernetes clusters.\n\nSignificant proficiency in Python. Experience working with GCP is preferrable.\n\nAbility to work in cross functional teams, have team-work mindset, self-motivation.\n\nExcellent written and verbal communication skills in English.\n\nAdditional Desirable Qualification.\n\nSolid grounding in statistics, probability theory, data modelling, machine learning algorithms and software development techniques and languages used to implement analytics solutions.\n\nExtensive background in statistical analysis and modeling (distributions, hypothesis testing, probability theory, etc.).\n\nCORE Competencies.\nJob skills required: English, Python, Software Development, NoSQL, Statistical Analysis, ETL, Kubernetes\nJob skills preferred: SQL, Industry trends, Leadership Skill, Cloud Computing","description_format":"text","description_chars":2545,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-09-26T13:04:00Z"}],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":1,"expected_fill_days":16,"reasons":["seen:1","win:early"],"computed_at":"2026-09-28T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/pttep-machine-learning-engineer","json_url":"https://alion.io/job/pttep-machine-learning-engineer.json","meta":{"generated_at":"2026-09-28T05:58:49Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":4155,"day_limit":5000,"remaining_today":845,"minute_limit":60,"resets_at":"2026-09-29T00:00:00Z"}}}